Soumettre la recherche
Mettre en ligne
TexelTek - Andrew Levine - Hadoop World 2010
•
2 j'aime
•
1,149 vues
Cloudera, Inc.
Suivre
Hadoop Image Processing for Disaster Relief Andrew Levine TexelTek
Lire moins
Lire la suite
Technologie
Art & Photos
Signaler
Partager
Signaler
Partager
1 sur 16
Recommandé
Presentation by Sylvain Charbonnier during the lunch & learn sessions on Day 2, June 25 at the EarthCube All-Hands Meeting
AHM 2014: The Flow Simulation Tools on VHub
AHM 2014: The Flow Simulation Tools on VHub
EarthCube
Discovery Day 2017 is focused on technology’s contribution to the implementation of the VGGT and on addressing some of the world’s most pressing tenure related issues, resulting from the negative impact of climate change, violent conflicts, mass migration, and growing urbanization. Bringing together speakers from the government, the private sector, FAO, World Bank, European Commission Joint Research Centre, the Discovery Day 2017 aims to demonstrate how technology could contribute to improving governance of tenure through transparency, accountability, and gender equality in land administration. © FAO: http://www.fao.org
DISCOVERY DAY 2017: MAKE IT HAPPEN!
DISCOVERY DAY 2017: MAKE IT HAPPEN!
FAO
Hamed Alemohammad, Ph.D., Lead Geospatial Data Scientist, Radiant Earth Foundation: An intro to Remote Sensing and Machine Learning.
IMED 2018: An intro to Remote Sensing and Machine Learning
IMED 2018: An intro to Remote Sensing and Machine Learning
Louisa Diggs
Presentation of the UAE solar Atlas by Masdar Institute http://atlas.masdar.ac.ae/
The UAE solar Atlas
The UAE solar Atlas
IRENA Global Atlas
We show how deep learning can be effectively applied to remote sensing. Many problems we faced, solutions we have had discovered were highlighted too. Remotely sensed data, unlike other vision tasks are very challenging and posses extra difficulties. Objects are very small compared to the image size, and even small pixel sizes of 8*10 pixel can contain huge amount of informations. To the best of our knowledge there is no automated or simi-automated tool that uses deep learning to detect features from satellite imagery.
Using deep learning in remote sensing
Using deep learning in remote sensing
Mohamed Yousif
Overview ESA's Geohazards Exploitation Platform developped by Terradue.
2017 esa gep_overview
2017 esa gep_overview
ESA
Description of the ESA originated Geohasards Exploitation Platform (GEP) developed and operated by a European consortium led by Terradue (IT).
2017 01-12 esa-gep_overview
2017 01-12 esa-gep_overview
ESA
The Seismic Hazard Modeller’s Toolkit: An Open-Source Library for the Construction of Probabilistic Seismic Hazard Models
The Seismic Hazard Modeller’s Toolkit: An Open-Source Library for the Const...
The Seismic Hazard Modeller’s Toolkit: An Open-Source Library for the Const...
Global Earthquake Model Foundation
Recommandé
Presentation by Sylvain Charbonnier during the lunch & learn sessions on Day 2, June 25 at the EarthCube All-Hands Meeting
AHM 2014: The Flow Simulation Tools on VHub
AHM 2014: The Flow Simulation Tools on VHub
EarthCube
Discovery Day 2017 is focused on technology’s contribution to the implementation of the VGGT and on addressing some of the world’s most pressing tenure related issues, resulting from the negative impact of climate change, violent conflicts, mass migration, and growing urbanization. Bringing together speakers from the government, the private sector, FAO, World Bank, European Commission Joint Research Centre, the Discovery Day 2017 aims to demonstrate how technology could contribute to improving governance of tenure through transparency, accountability, and gender equality in land administration. © FAO: http://www.fao.org
DISCOVERY DAY 2017: MAKE IT HAPPEN!
DISCOVERY DAY 2017: MAKE IT HAPPEN!
FAO
Hamed Alemohammad, Ph.D., Lead Geospatial Data Scientist, Radiant Earth Foundation: An intro to Remote Sensing and Machine Learning.
IMED 2018: An intro to Remote Sensing and Machine Learning
IMED 2018: An intro to Remote Sensing and Machine Learning
Louisa Diggs
Presentation of the UAE solar Atlas by Masdar Institute http://atlas.masdar.ac.ae/
The UAE solar Atlas
The UAE solar Atlas
IRENA Global Atlas
We show how deep learning can be effectively applied to remote sensing. Many problems we faced, solutions we have had discovered were highlighted too. Remotely sensed data, unlike other vision tasks are very challenging and posses extra difficulties. Objects are very small compared to the image size, and even small pixel sizes of 8*10 pixel can contain huge amount of informations. To the best of our knowledge there is no automated or simi-automated tool that uses deep learning to detect features from satellite imagery.
Using deep learning in remote sensing
Using deep learning in remote sensing
Mohamed Yousif
Overview ESA's Geohazards Exploitation Platform developped by Terradue.
2017 esa gep_overview
2017 esa gep_overview
ESA
Description of the ESA originated Geohasards Exploitation Platform (GEP) developed and operated by a European consortium led by Terradue (IT).
2017 01-12 esa-gep_overview
2017 01-12 esa-gep_overview
ESA
The Seismic Hazard Modeller’s Toolkit: An Open-Source Library for the Construction of Probabilistic Seismic Hazard Models
The Seismic Hazard Modeller’s Toolkit: An Open-Source Library for the Const...
The Seismic Hazard Modeller’s Toolkit: An Open-Source Library for the Const...
Global Earthquake Model Foundation
Victoria M Gammino, Ph.D., MPH, Radiant Earth Foundation: Innovations and Challenges in the Use of Open-source Remote Sensing Data and Tools.
IMED 2018: Innovations and Challenges in the Use of Open-source Remote Sensin...
IMED 2018: Innovations and Challenges in the Use of Open-source Remote Sensin...
Louisa Diggs
Keynote for HIC 2014 – 11th International Conference on Hydroinformatics, New York, USA August 17 – 21, 2014 Time, Change and Habits in Geospatial-Temporal Information Standards Time and change are fundamental to our scientific understanding of the world. Standards for geospatial-temporal information exist but new needs outstrip current standards. Geospatial-temporal information includes capturing change in features and coverages and modeling the processes that inform change. Key standards for time, calendars, and temporal reference systems are in place. Time series modeling from the WaterML standard is a recent advance of high value to hydrology. The OGC Moving Features standard will establish an encoding format for changes in “rigid” features. Interoperability standards are needed for Coverages with values that change based on observations, analytical expressions, or simulations. Applying a coverage model to time-varying, fluid Earth systems was the topic of the ground breaking GALEON Interoperability Experiment. Standards developments for spatial-temporal process models is progressing with WPS, OpenMI and ESMF - supporting a Model Web concept. A robust framework for sharing geospatial-temporal information is now coming into place based on developments captured in standards by ISO, WMO, ITU, ICSU and OGC - including the newly established OGC Temporal domain working group. The new framework will enable capabilities in expressing and sharing scientific investigations including research on the emergence of forms over time. With these new capabilities we may come to understand Peirce’s observation that over time “all things have a tendency to take habits.”
Time, Change and Habits in Geospatial-Temporal Information Standards
Time, Change and Habits in Geospatial-Temporal Information Standards
George Percivall
Mapping the Tohoku 2011 Tsunami event with a remote sensing satellite constel...
Mapping the Tohoku 2011 Tsunami event with a remote sensing satellite constel...
Peter Löwe
A reference case for emerging Early Warning System Dissemination Services
Mapping the Tohoku 2011 Tsunami event with a remote sensing satellite constel...
Mapping the Tohoku 2011 Tsunami event with a remote sensing satellite constel...
Peter Löwe
EMME Earthquake Model of Middle East
EMME Earthquake Model of Middle East
EMME Earthquake Model of Middle East
Global Earthquake Model Foundation
Big Data, Data Mining, Information Mining for Earth Observation
Big Data, Data and Information Mining for Earth Observation
Big Data, Data and Information Mining for Earth Observation
Pier Giorgio Marchetti
Presentation to IGARSS 2015 Conference, July 205, Milan Italy. Part of invited session: Why Data Matters: Value of Stewardship and Knowledge Augmentation Services
Scientific Knowledge from Geospatial Observations
Scientific Knowledge from Geospatial Observations
George Percivall
UAVs are a disruptive technology bringing new geographic data and information to many application domains. UASs are similar to other geographic imagery systems so existing frameworks are applicable. But the diversity of UAVs as platforms along with the diversity of available sensors are presenting challenges in the processing and creation of geospatial products. Efficient processing and dissemination of the data is achieved using software and systems that implement open standards. The challenges identified point to the need for use of existing standards and extending standards. Results from the use of the OGC Sensor Web Enablement set of standards are presented. Next steps in the progress of UAVs and UASs may follow the path of open data, open source and open standards.
Common Approach for UAS Data Geoprocessing
Common Approach for UAS Data Geoprocessing
George Percivall
Rs
Rs
Samarthi Praveen
introduction to gis&remote snsing.
Remote sensing & Gis
Remote sensing & Gis
gopichand's
The latest results from the EMME project presented during the launch event of the OpenQuake platform in Pavia on January 21, 2015.
EMME project_OQRelease
EMME project_OQRelease
Global Earthquake Model Foundation
GEM Risk: main achievements during the first implementation phase
GEM Risk: main achievements during the first implementation phase
GEM Risk: main achievements during the first implementation phase
Global Earthquake Model Foundation
GEM’S HAZARD PRODUCTS: OUTCOMES AND APPLICATIONS
GEM’s hazard products: outcomes and applications
GEM’s hazard products: outcomes and applications
Global Earthquake Model Foundation
European and other countries are at increasing risk for new or re-emerging vector-borne diseases. Among the top ten vector-borne diseases with greatest potential to affect European citizens are Dengue fever, Chikungunya, Hantavirus, and Crimean-Congo hemorrhagic fever. Despite the risk of disease transmission, many vectors like the Asian tiger mosquito or ticks are also a nuisance in daily life. The examination of disease vector spread and a better understanding of spatio-temporal patterns in disease transmission and diffusion is greatly facilitated by Geoinformatics. New methods including the use of high resolution time series from space in spatial models enable us to predict species invasion and survival, and to assess potential health risks. Geoinformatics is able to address the increasing challenge for human and veterinary public health not only in Europe, but across the globe, assisting decision makers and public health authorities to develop surveillance plans and vector control.
Tracking emerging diseases from space: Geoinformatics for human health
Tracking emerging diseases from space: Geoinformatics for human health
Markus Neteler
Expertise over Satellite Imaging Areas under Satellite Image Processing Projects Benefits of Satellite Imaging
Satellite Image Processing Projects Research Help
Satellite Image Processing Projects Research Help
Matlab Simulation
Introduction to Remote sensing
Introduction to remote sensing and gis
Introduction to remote sensing and gis
Mohsin Siddique
International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications
International Refereed Journal of Engineering and Science (IRJES)
International Refereed Journal of Engineering and Science (IRJES)
irjes
Using GEM’S Tools and Datasets for Calculating Hazard Across the Globe
Using GEM’S Tools and Datasets for Calculating Hazard Across the Globe
Using GEM’S Tools and Datasets for Calculating Hazard Across the Globe
Global Earthquake Model Foundation
Presentation Location and Context World, 2015. Palo Alto, CA November 3-4, 2015. Abstract: Creating useful local context requires big data platforms and marketplaces. Contextual awareness is relevant to location based marketing, first responders, urban planners and many others. Location-aware mobile devices are revolutionizing how consumers and brands interact in the physical world. Situational awareness is a key element to efficiently handling any emergency response. In all cases, big data processing and high velocity streaming of location based data creates the richest contextual awareness. Data from many sources including IoT devices, sensor webs, surveillance and crowdsourcing are combined with semantically-rich urban and indoor data models. The resulting context information is delivered to and shared by mobile devices in connected and disconnected operations. Standards play a key role in establishing context platforms and marketplaces. Successful approaches will consolidate data from ubiquitous sensing technologies on a common space-time basis to enabled context-aware analysis of environmental and social dynamics.
Big Data for Local Context
Big Data for Local Context
George Percivall
Providing the best online coaching ,study material, guidance and solutions for CBSE UGC NET- JRF/ LS and ARS - NET in Environmental Sciences
Basic remote sensing and gis
Basic remote sensing and gis
SatGur Masters Academy
Talk given at the Sensor and Sensor Network Technologies in Environmental Monitoring workshop. May 8-9th, 2013 Canberra
Gigapixel resolution imaging for near-remote sensing and phenomics
Gigapixel resolution imaging for near-remote sensing and phenomics
TimeScience
The second EAG (Expert Advisory Group) meeting was held on February 5th, 2019 in Geneva. Terradue as EAG member was invited to present on solutions supporting the GEO vision for Knowledge Hubs
GEO Expert Advisory Group - ESA Thematic Exploitation Platforms - Geohazards
GEO Expert Advisory Group - ESA Thematic Exploitation Platforms - Geohazards
terradue
Contenu connexe
Tendances
Victoria M Gammino, Ph.D., MPH, Radiant Earth Foundation: Innovations and Challenges in the Use of Open-source Remote Sensing Data and Tools.
IMED 2018: Innovations and Challenges in the Use of Open-source Remote Sensin...
IMED 2018: Innovations and Challenges in the Use of Open-source Remote Sensin...
Louisa Diggs
Keynote for HIC 2014 – 11th International Conference on Hydroinformatics, New York, USA August 17 – 21, 2014 Time, Change and Habits in Geospatial-Temporal Information Standards Time and change are fundamental to our scientific understanding of the world. Standards for geospatial-temporal information exist but new needs outstrip current standards. Geospatial-temporal information includes capturing change in features and coverages and modeling the processes that inform change. Key standards for time, calendars, and temporal reference systems are in place. Time series modeling from the WaterML standard is a recent advance of high value to hydrology. The OGC Moving Features standard will establish an encoding format for changes in “rigid” features. Interoperability standards are needed for Coverages with values that change based on observations, analytical expressions, or simulations. Applying a coverage model to time-varying, fluid Earth systems was the topic of the ground breaking GALEON Interoperability Experiment. Standards developments for spatial-temporal process models is progressing with WPS, OpenMI and ESMF - supporting a Model Web concept. A robust framework for sharing geospatial-temporal information is now coming into place based on developments captured in standards by ISO, WMO, ITU, ICSU and OGC - including the newly established OGC Temporal domain working group. The new framework will enable capabilities in expressing and sharing scientific investigations including research on the emergence of forms over time. With these new capabilities we may come to understand Peirce’s observation that over time “all things have a tendency to take habits.”
Time, Change and Habits in Geospatial-Temporal Information Standards
Time, Change and Habits in Geospatial-Temporal Information Standards
George Percivall
Mapping the Tohoku 2011 Tsunami event with a remote sensing satellite constel...
Mapping the Tohoku 2011 Tsunami event with a remote sensing satellite constel...
Peter Löwe
A reference case for emerging Early Warning System Dissemination Services
Mapping the Tohoku 2011 Tsunami event with a remote sensing satellite constel...
Mapping the Tohoku 2011 Tsunami event with a remote sensing satellite constel...
Peter Löwe
EMME Earthquake Model of Middle East
EMME Earthquake Model of Middle East
EMME Earthquake Model of Middle East
Global Earthquake Model Foundation
Big Data, Data Mining, Information Mining for Earth Observation
Big Data, Data and Information Mining for Earth Observation
Big Data, Data and Information Mining for Earth Observation
Pier Giorgio Marchetti
Presentation to IGARSS 2015 Conference, July 205, Milan Italy. Part of invited session: Why Data Matters: Value of Stewardship and Knowledge Augmentation Services
Scientific Knowledge from Geospatial Observations
Scientific Knowledge from Geospatial Observations
George Percivall
UAVs are a disruptive technology bringing new geographic data and information to many application domains. UASs are similar to other geographic imagery systems so existing frameworks are applicable. But the diversity of UAVs as platforms along with the diversity of available sensors are presenting challenges in the processing and creation of geospatial products. Efficient processing and dissemination of the data is achieved using software and systems that implement open standards. The challenges identified point to the need for use of existing standards and extending standards. Results from the use of the OGC Sensor Web Enablement set of standards are presented. Next steps in the progress of UAVs and UASs may follow the path of open data, open source and open standards.
Common Approach for UAS Data Geoprocessing
Common Approach for UAS Data Geoprocessing
George Percivall
Rs
Rs
Samarthi Praveen
introduction to gis&remote snsing.
Remote sensing & Gis
Remote sensing & Gis
gopichand's
The latest results from the EMME project presented during the launch event of the OpenQuake platform in Pavia on January 21, 2015.
EMME project_OQRelease
EMME project_OQRelease
Global Earthquake Model Foundation
GEM Risk: main achievements during the first implementation phase
GEM Risk: main achievements during the first implementation phase
GEM Risk: main achievements during the first implementation phase
Global Earthquake Model Foundation
GEM’S HAZARD PRODUCTS: OUTCOMES AND APPLICATIONS
GEM’s hazard products: outcomes and applications
GEM’s hazard products: outcomes and applications
Global Earthquake Model Foundation
European and other countries are at increasing risk for new or re-emerging vector-borne diseases. Among the top ten vector-borne diseases with greatest potential to affect European citizens are Dengue fever, Chikungunya, Hantavirus, and Crimean-Congo hemorrhagic fever. Despite the risk of disease transmission, many vectors like the Asian tiger mosquito or ticks are also a nuisance in daily life. The examination of disease vector spread and a better understanding of spatio-temporal patterns in disease transmission and diffusion is greatly facilitated by Geoinformatics. New methods including the use of high resolution time series from space in spatial models enable us to predict species invasion and survival, and to assess potential health risks. Geoinformatics is able to address the increasing challenge for human and veterinary public health not only in Europe, but across the globe, assisting decision makers and public health authorities to develop surveillance plans and vector control.
Tracking emerging diseases from space: Geoinformatics for human health
Tracking emerging diseases from space: Geoinformatics for human health
Markus Neteler
Expertise over Satellite Imaging Areas under Satellite Image Processing Projects Benefits of Satellite Imaging
Satellite Image Processing Projects Research Help
Satellite Image Processing Projects Research Help
Matlab Simulation
Introduction to Remote sensing
Introduction to remote sensing and gis
Introduction to remote sensing and gis
Mohsin Siddique
International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications
International Refereed Journal of Engineering and Science (IRJES)
International Refereed Journal of Engineering and Science (IRJES)
irjes
Using GEM’S Tools and Datasets for Calculating Hazard Across the Globe
Using GEM’S Tools and Datasets for Calculating Hazard Across the Globe
Using GEM’S Tools and Datasets for Calculating Hazard Across the Globe
Global Earthquake Model Foundation
Presentation Location and Context World, 2015. Palo Alto, CA November 3-4, 2015. Abstract: Creating useful local context requires big data platforms and marketplaces. Contextual awareness is relevant to location based marketing, first responders, urban planners and many others. Location-aware mobile devices are revolutionizing how consumers and brands interact in the physical world. Situational awareness is a key element to efficiently handling any emergency response. In all cases, big data processing and high velocity streaming of location based data creates the richest contextual awareness. Data from many sources including IoT devices, sensor webs, surveillance and crowdsourcing are combined with semantically-rich urban and indoor data models. The resulting context information is delivered to and shared by mobile devices in connected and disconnected operations. Standards play a key role in establishing context platforms and marketplaces. Successful approaches will consolidate data from ubiquitous sensing technologies on a common space-time basis to enabled context-aware analysis of environmental and social dynamics.
Big Data for Local Context
Big Data for Local Context
George Percivall
Providing the best online coaching ,study material, guidance and solutions for CBSE UGC NET- JRF/ LS and ARS - NET in Environmental Sciences
Basic remote sensing and gis
Basic remote sensing and gis
SatGur Masters Academy
Tendances
(20)
IMED 2018: Innovations and Challenges in the Use of Open-source Remote Sensin...
IMED 2018: Innovations and Challenges in the Use of Open-source Remote Sensin...
Time, Change and Habits in Geospatial-Temporal Information Standards
Time, Change and Habits in Geospatial-Temporal Information Standards
Mapping the Tohoku 2011 Tsunami event with a remote sensing satellite constel...
Mapping the Tohoku 2011 Tsunami event with a remote sensing satellite constel...
Mapping the Tohoku 2011 Tsunami event with a remote sensing satellite constel...
Mapping the Tohoku 2011 Tsunami event with a remote sensing satellite constel...
EMME Earthquake Model of Middle East
EMME Earthquake Model of Middle East
Big Data, Data and Information Mining for Earth Observation
Big Data, Data and Information Mining for Earth Observation
Scientific Knowledge from Geospatial Observations
Scientific Knowledge from Geospatial Observations
Common Approach for UAS Data Geoprocessing
Common Approach for UAS Data Geoprocessing
Rs
Rs
Remote sensing & Gis
Remote sensing & Gis
EMME project_OQRelease
EMME project_OQRelease
GEM Risk: main achievements during the first implementation phase
GEM Risk: main achievements during the first implementation phase
GEM’s hazard products: outcomes and applications
GEM’s hazard products: outcomes and applications
Tracking emerging diseases from space: Geoinformatics for human health
Tracking emerging diseases from space: Geoinformatics for human health
Satellite Image Processing Projects Research Help
Satellite Image Processing Projects Research Help
Introduction to remote sensing and gis
Introduction to remote sensing and gis
International Refereed Journal of Engineering and Science (IRJES)
International Refereed Journal of Engineering and Science (IRJES)
Using GEM’S Tools and Datasets for Calculating Hazard Across the Globe
Using GEM’S Tools and Datasets for Calculating Hazard Across the Globe
Big Data for Local Context
Big Data for Local Context
Basic remote sensing and gis
Basic remote sensing and gis
Similaire à TexelTek - Andrew Levine - Hadoop World 2010
Talk given at the Sensor and Sensor Network Technologies in Environmental Monitoring workshop. May 8-9th, 2013 Canberra
Gigapixel resolution imaging for near-remote sensing and phenomics
Gigapixel resolution imaging for near-remote sensing and phenomics
TimeScience
The second EAG (Expert Advisory Group) meeting was held on February 5th, 2019 in Geneva. Terradue as EAG member was invited to present on solutions supporting the GEO vision for Knowledge Hubs
GEO Expert Advisory Group - ESA Thematic Exploitation Platforms - Geohazards
GEO Expert Advisory Group - ESA Thematic Exploitation Platforms - Geohazards
terradue
Landmap CETIS 2012
Landmap CETIS 2012
Bharti Gupta
Planet offers up-to-date, high-quality images of the entire earth from 150+ satellites. Learn how to build automated workflows that integrate your data with these images in various ways. You’ll see how to transform and analyze bands, blend your data with the most up-to-date satellite images, and create cloud-based workflows to deliver images automatically. We’ll walk through an example that overlays live transit data on an up-to-date basemap with minimal cloud coverage. Plus, see what’s in beta for FME 2018 and Planet basemaps.
Integration for Planet Satellite Imagery
Integration for Planet Satellite Imagery
Safe Software
sevt
sevt
Iryna Rozum
From gigapixel timelapse cameras to unmanned aerial vehicles to smartphones: ...
From gigapixel timelapse cameras to unmanned aerial vehicles to smartphones: ...
TimeScience
Presentation given for Whitham lab. July, 2016
TraitCapture: NextGen Monitoring and Visualization from seed to ecosystem
TraitCapture: NextGen Monitoring and Visualization from seed to ecosystem
TimeScience
Presentation by Dr Tim Brown Full webinar: https://www.youtube.com/watch?v=bl_7ClXhQlA&list=PLG25fMbdLRa5qsPiBGPaj2NHqPyG8X435&index=11 Individual snippet:https://youtu.be/PVf4zYNJlmM?list=PLG25fMbdLRa5qsPiBGPaj2NHqPyG8X435
From pixels to point clouds - Using drones,game engines and virtual reality t...
From pixels to point clouds - Using drones,game engines and virtual reality t...
ARDC
Goal andga oct01
Goal andga oct01
Clifford Stone
-
TRIDEC Cloud @ Tsunami Decision Support Systems 2015, 2-3 July 2015, Ispra, I...
TRIDEC Cloud @ Tsunami Decision Support Systems 2015, 2-3 July 2015, Ispra, I...
Martin Hammitzsch
Geospatial World Tour 2014: Emergency Conference. Napoli, 28 maggio 2014. La gestione del processo di acquisizione e gestione dati. Simone Colla, Hexagon Geospatial
GWT 2014: Emergency Conference - 03 la gestione del processo di acquisizione ...
GWT 2014: Emergency Conference - 03 la gestione del processo di acquisizione ...
Planetek Italia Srl
RedisConf19
Processing Real-Time Volcano Seismic Measurements Through Redis: David Chaves
Processing Real-Time Volcano Seismic Measurements Through Redis: David Chaves
Redis Labs
Talk given by Tim Brown at the annual Ecological Society of Australia, 2012 meeting in Melbourne, Australia. More info on the Gigavision project here: http://www.gigavision.org
Gigapixel imaging, ESA Australia, Dec 2012
Gigapixel imaging, ESA Australia, Dec 2012
TimeScience
Landslide identification using synthetic aperture radar change detection on the Google Earth Engine
CL#21-0488.pdf
CL#21-0488.pdf
KaderGomatique
The presentaiton provides an overview of land monitoring and analysis through the open foris tool
Collect earth & earth map
Collect earth & earth map
FAO
IU: Ezra Kissel, Akshay Dorwat, Jeremy Musser, Prakash Rajagopal, Rohit Khapare, Joseph Cottam, Martin Swany UW-Madison: Sam Batzli Director, WisconsinView SFASU: Paul Blackwell Exec. Comm., AmericaView
EODN-IDMS A distributed storage service for open access to Landsat data for n...
EODN-IDMS A distributed storage service for open access to Landsat data for n...
US-Ignite
Zhang UAV at USCID
Zhang UAV at USCID
Joseph Yu Zhang, E.I.T.
Matthias Lendholt's, Martin Hammitzsch's and Peter Löwe's presentation on the "Harmonization of Data Formats for Tsunami Simulation Products" at ISCRAM 2013 in Baden-Baden. 10th International Conference on Information Systems for Crisis Response and Management 12-15 May 2013, Baden-Baden, Germany
Harmonization of Data Formats for Tsunami Simulation Products
Harmonization of Data Formats for Tsunami Simulation Products
streamspotter
Explanatory material of NIED Disaster Information Sharing System which is developed by National Research Institute for Earth Science and Disaster Prevention (NIED), Japan
Explanatory material of NIED Disaster Information Sharing System
Explanatory material of NIED Disaster Information Sharing System
Tadashi Ise
Presentation given by Guido Lemoine EC-JRC-IPSC-SES-ISFEREA during UN-SPIDER Workshop, UN Campus Bonn, Germany 30 October 2007
Collaborative Geo-information Capturing To Support Emergency Response
Collaborative Geo-information Capturing To Support Emergency Response
UN-SPIDER
Similaire à TexelTek - Andrew Levine - Hadoop World 2010
(20)
Gigapixel resolution imaging for near-remote sensing and phenomics
Gigapixel resolution imaging for near-remote sensing and phenomics
GEO Expert Advisory Group - ESA Thematic Exploitation Platforms - Geohazards
GEO Expert Advisory Group - ESA Thematic Exploitation Platforms - Geohazards
Landmap CETIS 2012
Landmap CETIS 2012
Integration for Planet Satellite Imagery
Integration for Planet Satellite Imagery
sevt
sevt
From gigapixel timelapse cameras to unmanned aerial vehicles to smartphones: ...
From gigapixel timelapse cameras to unmanned aerial vehicles to smartphones: ...
TraitCapture: NextGen Monitoring and Visualization from seed to ecosystem
TraitCapture: NextGen Monitoring and Visualization from seed to ecosystem
From pixels to point clouds - Using drones,game engines and virtual reality t...
From pixels to point clouds - Using drones,game engines and virtual reality t...
Goal andga oct01
Goal andga oct01
TRIDEC Cloud @ Tsunami Decision Support Systems 2015, 2-3 July 2015, Ispra, I...
TRIDEC Cloud @ Tsunami Decision Support Systems 2015, 2-3 July 2015, Ispra, I...
GWT 2014: Emergency Conference - 03 la gestione del processo di acquisizione ...
GWT 2014: Emergency Conference - 03 la gestione del processo di acquisizione ...
Processing Real-Time Volcano Seismic Measurements Through Redis: David Chaves
Processing Real-Time Volcano Seismic Measurements Through Redis: David Chaves
Gigapixel imaging, ESA Australia, Dec 2012
Gigapixel imaging, ESA Australia, Dec 2012
CL#21-0488.pdf
CL#21-0488.pdf
Collect earth & earth map
Collect earth & earth map
EODN-IDMS A distributed storage service for open access to Landsat data for n...
EODN-IDMS A distributed storage service for open access to Landsat data for n...
Zhang UAV at USCID
Zhang UAV at USCID
Harmonization of Data Formats for Tsunami Simulation Products
Harmonization of Data Formats for Tsunami Simulation Products
Explanatory material of NIED Disaster Information Sharing System
Explanatory material of NIED Disaster Information Sharing System
Collaborative Geo-information Capturing To Support Emergency Response
Collaborative Geo-information Capturing To Support Emergency Response
Plus de Cloudera, Inc.
Partner Webinar for updates and news January 25th 2022
Partner Briefing_January 25 (FINAL).pptx
Partner Briefing_January 25 (FINAL).pptx
Cloudera, Inc.
This annual program recognizes organizations who are moving swiftly towards the future and building innovative solutions by making what was impossible yesterday, possible today. The winning organizations' implementations demonstrate outstanding achievements in fulfilling their mission, technical advancement, and overall impact. The 2021 Data Impact Awards recognize organizations' achievements with the Cloudera Data Platform in seven categories: Data Lifecycle Connection Data for Enterprise AI Cloud Innovation Security & Governance Leadership People First Data for Good Industry Transformation
Cloudera Data Impact Awards 2021 - Finalists
Cloudera Data Impact Awards 2021 - Finalists
Cloudera, Inc.
Cloudera is proud to present the 2020 Data Impact Awards Finalists. This annual program recognizes organizations running the Cloudera platform for the applications they've built and the impact their data projects have on their organizations, their industries, and the world. Nominations were evaluated by a panel of independent thought-leaders and expert industry analysts, who then selected the finalists and winners. Winners exemplify the most-cutting edge data projects and represent innovation and leadership in their respective industries.
2020 Cloudera Data Impact Awards Finalists
2020 Cloudera Data Impact Awards Finalists
Cloudera, Inc.
Cloudera Enterprise Data Cloud Event Vienna 1 Oct. 2019
Edc event vienna presentation 1 oct 2019
Edc event vienna presentation 1 oct 2019
Cloudera, Inc.
Cloudera Fast Forward Labs’ latest research report and prototype explore learning with limited labeled data. This capability relaxes the stringent labeled data requirement in supervised machine learning and opens up new product possibilities. It is industry invariant, addresses the labeling pain point and enables applications to be built faster and more efficiently.
Machine Learning with Limited Labeled Data 4/3/19
Machine Learning with Limited Labeled Data 4/3/19
Cloudera, Inc.
In this session, we will cover how to move beyond structured, curated reports based on known questions on known data, to an ad-hoc exploration of all data to optimize business processes and into the unknown questions on unknown data, where machine learning and statistically motivated predictive analytics are shaping business strategy.
Data Driven With the Cloudera Modern Data Warehouse 3.19.19
Data Driven With the Cloudera Modern Data Warehouse 3.19.19
Cloudera, Inc.
Watch this webinar to understand how Hortonworks DataFlow (HDF) has evolved into the new Cloudera DataFlow (CDF). Learn about key capabilities that CDF delivers such as - -Powerful data ingestion powered by Apache NiFi -Edge data collection by Apache MiNiFi -IoT-scale streaming data processing with Apache Kafka -Enterprise services to offer unified security and governance from edge-to-enterprise
Introducing Cloudera DataFlow (CDF) 2.13.19
Introducing Cloudera DataFlow (CDF) 2.13.19
Cloudera, Inc.
Cloudera’s Data Science Workbench (CDSW) is available for Hortonworks Data Platform (HDP) clusters for secure, collaborative data science at scale. During this webinar, we provide an introductory tour of CDSW and a demonstration of a machine learning workflow using CDSW on HDP.
Introducing Cloudera Data Science Workbench for HDP 2.12.19
Introducing Cloudera Data Science Workbench for HDP 2.12.19
Cloudera, Inc.
Join Cloudera as we outline how we use Cloudera technology to strengthen sales engagement, minimize marketing waste, and empower line of business leaders to drive successful outcomes.
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19
Cloudera, Inc.
Learn how organizations are deriving unique customer insights, improving product and services efficiency, and reducing business risk with a modern big data architecture powered by Cloudera on Azure. In this webinar, you see how fast and easy it is to deploy a modern data management platform—in your cloud, on your terms.
Leveraging the cloud for analytics and machine learning 1.29.19
Leveraging the cloud for analytics and machine learning 1.29.19
Cloudera, Inc.
Join us to learn about the challenges of legacy data warehousing, the goals of modern data warehousing, and the design patterns and frameworks that help to accelerate modernization efforts.
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19
Cloudera, Inc.
Learn how organizations are deriving unique customer insights, improving product and services efficiency, and reducing business risk with a modern big data architecture powered by Cloudera on AWS. In this webinar, you see how fast and easy it is to deploy a modern data management platform—in your cloud, on your terms.
Leveraging the Cloud for Big Data Analytics 12.11.18
Leveraging the Cloud for Big Data Analytics 12.11.18
Cloudera, Inc.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Modern Data Warehouse Fundamentals Part 3
Modern Data Warehouse Fundamentals Part 3
Cloudera, Inc.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Modern Data Warehouse Fundamentals Part 2
Modern Data Warehouse Fundamentals Part 2
Cloudera, Inc.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Modern Data Warehouse Fundamentals Part 1
Modern Data Warehouse Fundamentals Part 1
Cloudera, Inc.
Cloudera SDX is by no means no restricted to just the platform; it extends well beyond. In this webinar, we show you how Bardess Group’s Zero2Hero solution leverages the shared data experience to coordinate Cloudera, Trifacta, and Qlik to deliver complete customer insight.
Extending Cloudera SDX beyond the Platform
Extending Cloudera SDX beyond the Platform
Cloudera, Inc.
Join Cloudera Fast Forward Labs Research Engineer, Mike Lee Williams, to hear about their latest research report and prototype on Federated Learning. Learn more about what it is, when it’s applicable, how it works, and the current landscape of tools and libraries.
Federated Learning: ML with Privacy on the Edge 11.15.18
Federated Learning: ML with Privacy on the Edge 11.15.18
Cloudera, Inc.
451 Research Analyst Sheryl Kingstone, and Cloudera’s Steve Totman recently discussed how a growing number of organizations are replacing legacy Customer 360 systems with Customer Insights Platforms.
Analyst Webinar: Doing a 180 on Customer 360
Analyst Webinar: Doing a 180 on Customer 360
Cloudera, Inc.
In this webinar, you will learn how Cloudera and BAH riskCanvas can help you build a modern AML platform that reduces false positive rates, investigation costs, technology sprawl, and regulatory risk.
Build a modern platform for anti-money laundering 9.19.18
Build a modern platform for anti-money laundering 9.19.18
Cloudera, Inc.
How can companies integrate data science into their businesses more effectively? Watch this recorded webinar and demonstration to hear more about operationalizing data science with Cloudera Data Science Workbench on Cazena’s fully-managed cloud platform.
Introducing the data science sandbox as a service 8.30.18
Introducing the data science sandbox as a service 8.30.18
Cloudera, Inc.
Plus de Cloudera, Inc.
(20)
Partner Briefing_January 25 (FINAL).pptx
Partner Briefing_January 25 (FINAL).pptx
Cloudera Data Impact Awards 2021 - Finalists
Cloudera Data Impact Awards 2021 - Finalists
2020 Cloudera Data Impact Awards Finalists
2020 Cloudera Data Impact Awards Finalists
Edc event vienna presentation 1 oct 2019
Edc event vienna presentation 1 oct 2019
Machine Learning with Limited Labeled Data 4/3/19
Machine Learning with Limited Labeled Data 4/3/19
Data Driven With the Cloudera Modern Data Warehouse 3.19.19
Data Driven With the Cloudera Modern Data Warehouse 3.19.19
Introducing Cloudera DataFlow (CDF) 2.13.19
Introducing Cloudera DataFlow (CDF) 2.13.19
Introducing Cloudera Data Science Workbench for HDP 2.12.19
Introducing Cloudera Data Science Workbench for HDP 2.12.19
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19
Leveraging the cloud for analytics and machine learning 1.29.19
Leveraging the cloud for analytics and machine learning 1.29.19
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19
Leveraging the Cloud for Big Data Analytics 12.11.18
Leveraging the Cloud for Big Data Analytics 12.11.18
Modern Data Warehouse Fundamentals Part 3
Modern Data Warehouse Fundamentals Part 3
Modern Data Warehouse Fundamentals Part 2
Modern Data Warehouse Fundamentals Part 2
Modern Data Warehouse Fundamentals Part 1
Modern Data Warehouse Fundamentals Part 1
Extending Cloudera SDX beyond the Platform
Extending Cloudera SDX beyond the Platform
Federated Learning: ML with Privacy on the Edge 11.15.18
Federated Learning: ML with Privacy on the Edge 11.15.18
Analyst Webinar: Doing a 180 on Customer 360
Analyst Webinar: Doing a 180 on Customer 360
Build a modern platform for anti-money laundering 9.19.18
Build a modern platform for anti-money laundering 9.19.18
Introducing the data science sandbox as a service 8.30.18
Introducing the data science sandbox as a service 8.30.18
Dernier
Cisco CCNA
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
giselly40
Stay safe, grab a drink and join us virtually for our upcoming "GenAI Risks & Security" Meetup to hear about how to uncover critical GenAI risks and vulnerabilities, AI security considerations in every company, and how a CISO should navigate through GenAI Risks.
GenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdf
lior mazor
Breathing New Life into MySQL Apps With Advanced Postgres Capabilities
🐬 The future of MySQL is Postgres 🐘
🐬 The future of MySQL is Postgres 🐘
RTylerCroy
The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
Joaquim Jorge
Enterprise Knowledge’s Urmi Majumder, Principal Data Architecture Consultant, and Fernando Aguilar Islas, Senior Data Science Consultant, presented "Driving Behavioral Change for Information Management through Data-Driven Green Strategy" on March 27, 2024 at Enterprise Data World (EDW) in Orlando, Florida. In this presentation, Urmi and Fernando discussed a case study describing how the information management division in a large supply chain organization drove user behavior change through awareness of the carbon footprint of their duplicated and near-duplicated content, identified via advanced data analytics. Check out their presentation to gain valuable perspectives on utilizing data-driven strategies to influence positive behavioral shifts and support sustainability initiatives within your organization. In this session, participants gained answers to the following questions: - What is a Green Information Management (IM) Strategy, and why should you have one? - How can Artificial Intelligence (AI) and Machine Learning (ML) support your Green IM Strategy through content deduplication? - How can an organization use insights into their data to influence employee behavior for IM? - How can you reap additional benefits from content reduction that go beyond Green IM?
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
Enterprise Knowledge
Slides from the presentation on Machine Learning for the Arts & Humanities seminar at the University of Bologna (Digital Humanities and Digital Knowledge program)
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
Maria Levchenko
Imagine a world where information flows as swiftly as thought itself, making decision-making as fluid as the data driving it. Every moment is critical, and the right tools can significantly boost your organization’s performance. The power of real-time data automation through FME can turn this vision into reality. Aimed at professionals eager to leverage real-time data for enhanced decision-making and efficiency, this webinar will cover the essentials of real-time data and its significance. We’ll explore: FME’s role in real-time event processing, from data intake and analysis to transformation and reporting An overview of leveraging streams vs. automations FME’s impact across various industries highlighted by real-life case studies Live demonstrations on setting up FME workflows for real-time data Practical advice on getting started, best practices, and tips for effective implementation Join us to enhance your skills in real-time data automation with FME, and take your operational capabilities to the next level.
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
Safe Software
ICT role in 21 century education. How to ICT help in education
presentation ICT roal in 21st century education
presentation ICT roal in 21st century education
jfdjdjcjdnsjd
Presentation from Melissa Klemke from her talk at Product Anonymous in April 2024
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
Product Anonymous
Presented by Mike Hicks
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
ThousandEyes
BooK Now Call us at +918448380779 to hire a gorgeous and seductive call girl for sex. Take a Delhi Escort Service. The help of our escort agency is mostly meant for men who want sexual Indian Escorts In Delhi NCR. It should be noted that any impersonator will get 100 attention from our Young Girls Escorts in Delhi. They will assume the position of reliable allies. VIP Call Girl With Original Photos Book Tonight +918448380779 Our Cheap Price 1 Hour not available 2 Hours 5000 Full Night 8000 TAG: Call Girls in Delhi, Noida, Gurgaon, Ghaziabad, Connaught Place, Greater Kailash Delhi, Lajpat Nagar Delhi, Mayur Vihar Delhi, Chanakyapuri Delhi, New Friends Colony Delhi, Majnu Ka Tilla, Karol Bagh, Malviya Nagar, Saket, Khan Market, Noida Sector 18, Noida Sector 76, Noida Sector 51, Gurgaon Mg Road, Iffco Chowk Gurgaon, Rajiv Chowk Gurgaon All Delhi Ncr Free Home Deliver
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
Delhi Call girls
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
naman860154
I've been in the field of "Cyber Security" in its many incarnations for about 25 years. In that time I've learned some lessons, some the hard way. Here are my slides presented at BSides New Orleans in April 2024.
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
Rafal Los
With more memory available, system performance of three Dell devices increased, which can translate to a better user experience Conclusion When your system has plenty of RAM to meet your needs, you can efficiently access the applications and data you need to finish projects and to-do lists without sacrificing time and focus. Our test results show that with more memory available, three Dell PCs delivered better performance and took less time to complete the Procyon Office Productivity benchmark. These advantages translate to users being able to complete workflows more quickly and multitask more easily. Whether you need the mobility of the Latitude 5440, the creative capabilities of the Precision 3470, or the high performance of the OptiPlex Tower Plus 7010, configuring your system with more RAM can help keep processes running smoothly, enabling you to do more without compromising performance.
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
Principled Technologies
Three things you will take away from the session: • How to run an effective tenant-to-tenant migration • Best practices for before, during, and after migration • Tips for using migration as a springboard to prepare for Copilot in Microsoft 365 Main ideas: Migration Overview: The presentation covers the current reality of cross-tenant migrations, the triggers, phases, best practices, and benefits of a successful tenant migration Considerations: When considering a migration, it is important to consider the migration scope, performance, customization, flexibility, user-friendly interface, automation, monitoring, support, training, scalability, data integrity, data security, cost, and licensing structure Next Wave: The next wave of change includes the launch of Copilot, which requires businesses to be prepared for upcoming changes related to Copilot and the cloud, and to consolidate data and tighten governance ShareGate: ShareGate can help with pre-migration analysis, configurable migration tool, and automated, end-user driven collaborative governance
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
sammart93
As privacy and data protection regulations evolve rapidly, organizations operating in multiple jurisdictions face mounting challenges to ensure compliance and safeguard customer data. With state-specific privacy laws coming up in multiple states this year, it is essential to understand what their unique data protection regulations will require clearly. How will data privacy evolve in the US in 2024? How to stay compliant? Our panellists will guide you through the intricacies of these states' specific data privacy laws, clarifying complex legal frameworks and compliance requirements. This webinar will review: - The essential aspects of each state's privacy landscape and the latest updates - Common compliance challenges faced by organizations operating in multiple states and best practices to achieve regulatory adherence - Valuable insights into potential changes to existing regulations and prepare your organization for the evolving landscape
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc
Tech Trends Report 2024 Future Today Institute
Tech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdf
hans926745
Abhishek Deb(1), Mr Abdul Kalam(2) M. Des (UX) , School of Design, DIT University , Dehradun. This paper explores the future potential of AI-enabled smartphone processors, aiming to investigate the advancements, capabilities, and implications of integrating artificial intelligence (AI) into smartphone technology. The research study goals consist of evaluating the development of AI in mobile phone processors, analyzing the existing state as well as abilities of AI-enabled cpus determining future patterns as well as chances together with reviewing obstacles as well as factors to consider for more growth.
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
debabhi2
Explore the leading Large Language Models (LLMs) and their capabilities with a comprehensive evaluation. Dive into their performance, architecture, and applications to gain insights into the state-of-the-art in natural language processing. Discover which LLM best suits your needs and stay ahead in the world of AI-driven language understanding.
Evaluating the top large language models.pdf
Evaluating the top large language models.pdf
ChristopherTHyatt
Read about the journey the Adobe Experience Manager team has gone through in order to become and scale API-first throughout the organisation.
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
Radu Cotescu
Dernier
(20)
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
GenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdf
🐬 The future of MySQL is Postgres 🐘
🐬 The future of MySQL is Postgres 🐘
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
presentation ICT roal in 21st century education
presentation ICT roal in 21st century education
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
Tech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdf
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
Evaluating the top large language models.pdf
Evaluating the top large language models.pdf
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
TexelTek - Andrew Levine - Hadoop World 2010
1.
OPEN CLOUD CONSORTIUM IMAGE PROCESSING FOR DISASTER RELIEF Image Cache and Image Delta
2.
GOALS FOR PROCESSING MAP IMAGERY • Make imagery available for Disaster Relief workers over the web • Provide a mechanism for large scale image processing Satellite/Map Imagery •
Provide image deltas for temporally different and geospaJally idenJcal image sets
3.
• Source imagery can be very large – New image formats can be ~2G – Compare image sets easily • New data daily – NASA E01 mission tasking for fires and floods •
Pass over areas about every 3rd day • High availability for results HaiJ image: 18,878px by 34,782px TOOLS AND THE PROCESSING PLATFORM MOTIVATION FOR CLOUD IMPLEMENTATION
4.
USE CASES FOR THIS FRAMEWORK • Disasters – Fires – Floods – Earthquakes – DeforestaJon – Drought – War/Refugees – Tornados • Other Processing – Medical Imagery – Anomaly DetecJon – Full MoJon Video – Tracking – Digital Cinema
5.
TOOLS AND THE PROCESSING PLATFORM • OCCTestbed pla^orm – Resources for processing large data –
Testbed of mulJple clouds – UIC cloud is 32 nodes • Quad Core, 16GB RAM, GigE, HDFS on 256GB • Apache Hadoop: MapReduce and HBase – Algorithm adheres to MapReduce framework – hcp://hadoop.apache.org/ • OCC Image Processing tools (open source) – hcp://code.google.com/p/matsu‐project/ – Image comparison
6.
INTERFACING WITH RESULTS • Open GeospaJal ConsorJum Web Map Service – Images available through OGCWMS open specificaJon –
hcp://www.opengeospaJal.org/ • OCC WMS Servlet (open source) – hcp://code.google.com/p/matsu‐project/ • Various Map Viewing Tools – OpenLayers, Google Maps, others
7.
ARAL SEA 1989 AND 2008
8.
ZOOM LEVELS / BOUNDS Zoom Level 1: 4 images Zoom Level 2: 16 images Zoom Level 3: 64 images Zoom Level 4: 256 images
9.
Mapper Input Key: Bounding Box Mapper Input Value: Mapper Output Key: Bounding Box Mapper Output Value: Mapper resizes and/or cuts up the original image into pieces to output Bounding Boxes (minx = ‐135.0 miny = 45.0 maxx = ‐112.5 maxy = 67.5) Step 1: Input to Mapper Step 2: Processing in Mapper Step 3: Mapper Output Mapper Output Key: Bounding Box Mapper Output Value: Mapper Output Key: Bounding Box Mapper Output Value: Mapper Output Key: Bounding Box Mapper Output Value: Mapper Output Key: Bounding Box Mapper Output Value: Mapper Output Key: Bounding Box Mapper Output Value: Mapper Output Key: Bounding Box Mapper Output Value: Mapper Output Key: Bounding Box Mapper Output Value: Build Tile Cache in the Cloud ‐ Mapper
10.
Reducer Key Input: Bounding Box (minx = ‐45.0 miny = ‐2.8125 maxx = ‐43.59375 maxy = ‐2.109375) Reducer Value Input: Step 1: Input to Reducer … Step 2: Reducer Output Assemble Images based on bounding box • Output to HBase • Builds up Layers for WMS for various datasets Build Tile Cache in the Cloud ‐ Reducer
11.
Mapper Input Key: Bounding Box Mapper Input Value: Mapper Output Key: Bounding Box Mapper Output Value: Mapper resizes and/or cuts up the original image into pieces to output Bounding Boxes (minx = ‐135.0 miny = 45.0 maxx = ‐112.5 maxy = 67.5) Step 1: Input to Mapper Step 2: Processing in Mapper Step 3: Mapper Output Mapper Output Key: Bounding Box Mapper Output Value: Mapper Output Key: Bounding Box Mapper Output Value: Mapper Output Key: Bounding Box Mapper Output Value: Mapper Output Key: Bounding Box Mapper Output Value: Mapper Output Key: Bounding Box Mapper Output Value: Mapper Output Key: Bounding Box Mapper Output Value: Mapper Output Key: Bounding Box Mapper Output Value: + Timestamp + Timestamp + Timestamp + Timestamp + Timestamp + Timestamp + Timestamp + Timestamp + Timestamp Image Processing in the Cloud ‐ Mapper
12.
Reducer Key Input: Bounding Box (minx = ‐45.0 miny = ‐2.8125 maxx = ‐43.59375 maxy = ‐2.109375) Reducer Value Input: Step 1: Input to Reducer … … Step 2: Process difference in Reducer Assemble Images based on Jmestamps and compared Result is a delta of the two Images Step 3: Reducer Output All images go to different map layers set of images for display in WMS Timestamp 1 Set Timestamp 2 Set Delta Set Image Processing in the Cloud ‐ Reducer
13.
GULF OIL SPILL Day 115 Day 128 Delta
14.
SAMPLES / FLOODS IN PAKISTAN 2010 day 197 2010 day 263 Delta
15.
SAMPLES / FLOODS IN PAKISTAN 2010 day 197 2010 day 263 Delta
16.
HBASE TABLES • OGC WMS Query translates to HBase scheme – Layers, Styles, ProjecJon, Size • Table name: WMS Layer – Row ID: Bounding Box of image ‐Column Family: Style Name and ProjecJon ‐Column Qualifier: Width x Height ‐Value: Buffered Image