Conférence de Mme Denise Vaillancourt, directrice exécutive, Planification, Marketing et Communications de la STM, prononcée le samedi 24 septembre 2011 au Hyatt Regency de Montréal dans le cadre de la 6e édition de C, le colloque annuel de la SQPRP organisé par les jeunes professionnels.
The document discusses improving relations between academia and industry, specifically Microsoft and academia. It describes Microsoft's work in computer vision and the process of transferring technology from research to products. It also outlines Microsoft's programs for collaborating with academia. Finally, it proposes ways to strengthen relations such as improving access to tutorials and libraries, researcher training, and increasing information sharing between industry and academia.
The document discusses new trends in jointly reconstructing 3D scenes and recognizing objects within scenes. It describes how high-level semantics can help solve geometric ambiguities, and how object detections and their geometric attributes provide constraints for estimating scene layout. Recent works have shown that injecting semantics into reconstruction allows accurate 3D models to be achieved from only a few images, initiating a new trend where large-scale categorization meets 3D modeling.
The document discusses new trends in jointly reconstructing 3D scenes and recognizing objects within scenes. It describes how high-level semantics can help solve geometric ambiguities, and how object detections and their geometric attributes provide constraints for estimating scene layout. Recent works have shown that injecting semantics into reconstruction allows accurate 3D models to be achieved from only a few images, initiating a new trend where large-scale categorization meets 3D modeling.
Conférence de Mme Denise Vaillancourt, directrice exécutive, Planification, Marketing et Communications de la STM, prononcée le samedi 24 septembre 2011 au Hyatt Regency de Montréal dans le cadre de la 6e édition de C, le colloque annuel de la SQPRP organisé par les jeunes professionnels.
The document discusses improving relations between academia and industry, specifically Microsoft and academia. It describes Microsoft's work in computer vision and the process of transferring technology from research to products. It also outlines Microsoft's programs for collaborating with academia. Finally, it proposes ways to strengthen relations such as improving access to tutorials and libraries, researcher training, and increasing information sharing between industry and academia.
The document discusses new trends in jointly reconstructing 3D scenes and recognizing objects within scenes. It describes how high-level semantics can help solve geometric ambiguities, and how object detections and their geometric attributes provide constraints for estimating scene layout. Recent works have shown that injecting semantics into reconstruction allows accurate 3D models to be achieved from only a few images, initiating a new trend where large-scale categorization meets 3D modeling.
The document discusses new trends in jointly reconstructing 3D scenes and recognizing objects within scenes. It describes how high-level semantics can help solve geometric ambiguities, and how object detections and their geometric attributes provide constraints for estimating scene layout. Recent works have shown that injecting semantics into reconstruction allows accurate 3D models to be achieved from only a few images, initiating a new trend where large-scale categorization meets 3D modeling.
This document contains lecture notes on asymptotic notation for analyzing algorithms. It defines big O, Ω, and Θ notation for describing the worst-case, best-case, and average-case time complexity of algorithms. It explains that these notations describe the upper and lower bounds of the growth rate of an algorithm's run time as the problem size increases. The document also provides examples of using asymptotic notation to classify common functions and discusses properties like how complexity is affected by addition, subtraction, multiplication, and more.
05 structured prediction and energy minimization part 2zukun
The document summarizes branch-and-bound search algorithms for solving structured prediction problems. It discusses that branch-and-bound search implicitly enumerates solutions to find the globally optimal solution. It works by partitioning the solution space into active and closed nodes, taking an active node and partitioning it further, then evaluating bounds to determine if nodes can be closed. Two examples are described: efficient subwindow search for object detection, and branch-and-mincut for binary image segmentation.
Describing People: A Poselet-based approach to attribute classificationzukun
The document summarizes prior work on poselets and attributes for describing people in images. It discusses how poselets were introduced in 2009 and have since been applied to tasks like segmentation, action recognition, and categorization. It also reviews over 20 prior works from 1990-2011 on discovering and learning attributes from text, images, motion capture data, and for tasks such as image retrieval, active learning, and determining gender. The goal of the current work is to extract attributes from images using a poselet-based approach.
The document discusses a theory about the computational function of the ventral stream in visual cortex. The theory proposes that:
1. The goal of the ventral stream is to learn visual transformations like translations during development to achieve invariance to those transformations.
2. A hierarchical architecture can reduce storage requirements by factorizing transformations into subgroups like translations and other transformations.
3. Evolution selected a hierarchical architecture and receptive field sizes that allow areas to learn specific transformations like translations in early areas and more complex transformations in higher areas.
4. Hebbian learning shapes tuning properties in each area to match the transformations learned in that area, from oriented bars to complex shape tuning.
The theory aims to explain properties of visual
Cvpr2007 object category recognition p2 - part based modelszukun
The document summarizes part-based models for object recognition. It discusses representing objects as a set of parts with specific locations and appearances. Computational complexity arises from the large number of possible part assignments. The document reviews different approaches for modeling part location and appearance to achieve invariance while maintaining tractability. It also discusses techniques for efficient recognition using these models.
Computer vision techniques are increasingly being used in astronomy to assist with tasks like identifying unknown celestial objects in images, improving image quality by removing atmospheric distortions, detecting exoplanets, classifying galaxies and stars, and analyzing cosmological images and detecting cosmic rays. Key applications include an automated system called Astrometry.net that can identify stars and unknown objects in images, deblurring techniques to counteract the distorting effects of Earth's atmosphere on images, and machine learning algorithms to help classify galaxies and stars as well as detect exoplanets. Future areas of development may involve using computer vision for cosmological analysis and classifying different types of cosmic rays.
The document discusses open problems and challenges in computer vision, including instance recognition for untextured objects, object recognition informed by 3D shape and materials, and fine-grained visual categorization. It presents mini-Hilbert problems such as developing visual representations to enable instance and category recognition for smooth untextured objects and wiry objects. The document also discusses material recognition and 3D shape recovery from images as areas requiring further research progress.
ECCV2010 tutorial: statisitcal and structural recognition of human actions pa...zukun
The 11th European Conference on Computer Vision was held from September 5-10, 2010 in Hersonissos, Heraklion, Crete, Greece. The conference included tutorials on topics such as statistical and structural recognition of human actions. Motion capture and analysis has been an area of interest dating back to early Renaissance studies of human anatomy and biomechanics. Modern applications of human action recognition include motion capture for animation, video editing, unusual activity detection in surveillance video, and large-scale video search enabled by advances in computer vision techniques.
The document discusses improving 3D scene understanding from images by incorporating stronger geometric constraints and reasoning. It suggests moving from qualitative, low-level representations to more quantitative representations that model precise boundaries, interposition, and depth ordering. This could allow combining reasoning about both geometric relations and semantic labels. Several challenges are noted, such as how to generate and search the large hypothesis space in a tractable way while avoiding early decisions, and how to represent constraints in a general way. Overall, the goal is to develop techniques that achieve true integration of geometric and semantic cues for scene interpretation.
Devoxx france 2014 - Outils du manager - Youen ChénéSaagie
Vous avez tous connu des bons ou (plus souvent) des mauvais managers dans votre carrière. Au gré de la croissance de votre société, de réorganisations ou de rachats, il arrive pour de bonnes ou de mauvaises raisons que vous-même teniez un rôle de management. Un rôle pas forcément à l'honneur dans notre communauté.
Le management, comme le développement, se base aussi sur des pratiques et des techniques. Voici une revue d'outils pragmatique et simple à mettre en place pour vous améliorer dans votre (nouveau) role de manager.
This document summarizes key concepts from CS 221 lecture 5 on hidden Markov models and temporal filtering. The lecture covered Markov chains, hidden Markov models, and particle filtering for approximate inference in hidden Markov models. Hidden Markov models extend Markov chains to allow for hidden states that are observed indirectly through emissions. Particle filtering uses samples or "particles" to represent the distribution over hidden states and approximate inference.
ECCV2010: feature learning for image classification, part 3zukun
The document discusses sparse coding techniques for image classification. It introduces two views of sparse coding - the topic model view where each basis represents a topic, and the geometric view where bases represent anchor points on a data manifold. A theoretical framework called local coordinate coding connects coding to nonlinear function learning. The document also describes practical coding methods like locality-constrained linear coding and super-vector coding, and their application to improving bag-of-words models for image classification.
The document discusses several topics related to computer vision and object recognition. It begins by questioning what would happen if object recognition and segmentation were solved. It notes that this would only solve a small part of scene understanding, as images tell complex stories similar to written language. It then discusses how to give effective presentations, including preparing, delivering talks with confidence while acknowledging limitations, and practicing. It concludes by providing an agenda for the next class meeting covering several papers on topics like scene understanding, object detection, and sketch recognition.
This document introduces visualization and summarizes three key libraries for scientific visualization - VTK, TVTK, and MayaVi2. It provides an overview of each library and examples of creating 3D visualizations with TVTK's visual and mlab tools, including visualizing spheres, boxes, animating a bouncing ball, and plotting curves in 3D space. The document is intended as an introduction for scientists and engineers to get started with 3D data visualization.
Principal component analysis and matrix factorizations for learning (part 1) ...zukun
This document discusses principal component analysis (PCA) and matrix factorizations for learning. It provides an overview of PCA and singular value decomposition (SVD), their history and applications. PCA and SVD are widely used techniques for dimensionality reduction and data transformation. The document also discusses how PCA relates to other methods like spectral clustering and correspondence analysis.
MEDIAPOST, leader en France de la communication de proximiteMEDIAPOST
MEDIAPOST, expert du Marketing Relationnel et de la communication ciblee en boite aux lettres.
MEDIAPOST, un acteur de terrain ancré dans la proximité, une entreprise en prise directe avec son environnement, des engagements forts pour le développement responsable.
This document contains lecture notes on asymptotic notation for analyzing algorithms. It defines big O, Ω, and Θ notation for describing the worst-case, best-case, and average-case time complexity of algorithms. It explains that these notations describe the upper and lower bounds of the growth rate of an algorithm's run time as the problem size increases. The document also provides examples of using asymptotic notation to classify common functions and discusses properties like how complexity is affected by addition, subtraction, multiplication, and more.
05 structured prediction and energy minimization part 2zukun
The document summarizes branch-and-bound search algorithms for solving structured prediction problems. It discusses that branch-and-bound search implicitly enumerates solutions to find the globally optimal solution. It works by partitioning the solution space into active and closed nodes, taking an active node and partitioning it further, then evaluating bounds to determine if nodes can be closed. Two examples are described: efficient subwindow search for object detection, and branch-and-mincut for binary image segmentation.
Describing People: A Poselet-based approach to attribute classificationzukun
The document summarizes prior work on poselets and attributes for describing people in images. It discusses how poselets were introduced in 2009 and have since been applied to tasks like segmentation, action recognition, and categorization. It also reviews over 20 prior works from 1990-2011 on discovering and learning attributes from text, images, motion capture data, and for tasks such as image retrieval, active learning, and determining gender. The goal of the current work is to extract attributes from images using a poselet-based approach.
The document discusses a theory about the computational function of the ventral stream in visual cortex. The theory proposes that:
1. The goal of the ventral stream is to learn visual transformations like translations during development to achieve invariance to those transformations.
2. A hierarchical architecture can reduce storage requirements by factorizing transformations into subgroups like translations and other transformations.
3. Evolution selected a hierarchical architecture and receptive field sizes that allow areas to learn specific transformations like translations in early areas and more complex transformations in higher areas.
4. Hebbian learning shapes tuning properties in each area to match the transformations learned in that area, from oriented bars to complex shape tuning.
The theory aims to explain properties of visual
Cvpr2007 object category recognition p2 - part based modelszukun
The document summarizes part-based models for object recognition. It discusses representing objects as a set of parts with specific locations and appearances. Computational complexity arises from the large number of possible part assignments. The document reviews different approaches for modeling part location and appearance to achieve invariance while maintaining tractability. It also discusses techniques for efficient recognition using these models.
Computer vision techniques are increasingly being used in astronomy to assist with tasks like identifying unknown celestial objects in images, improving image quality by removing atmospheric distortions, detecting exoplanets, classifying galaxies and stars, and analyzing cosmological images and detecting cosmic rays. Key applications include an automated system called Astrometry.net that can identify stars and unknown objects in images, deblurring techniques to counteract the distorting effects of Earth's atmosphere on images, and machine learning algorithms to help classify galaxies and stars as well as detect exoplanets. Future areas of development may involve using computer vision for cosmological analysis and classifying different types of cosmic rays.
The document discusses open problems and challenges in computer vision, including instance recognition for untextured objects, object recognition informed by 3D shape and materials, and fine-grained visual categorization. It presents mini-Hilbert problems such as developing visual representations to enable instance and category recognition for smooth untextured objects and wiry objects. The document also discusses material recognition and 3D shape recovery from images as areas requiring further research progress.
ECCV2010 tutorial: statisitcal and structural recognition of human actions pa...zukun
The 11th European Conference on Computer Vision was held from September 5-10, 2010 in Hersonissos, Heraklion, Crete, Greece. The conference included tutorials on topics such as statistical and structural recognition of human actions. Motion capture and analysis has been an area of interest dating back to early Renaissance studies of human anatomy and biomechanics. Modern applications of human action recognition include motion capture for animation, video editing, unusual activity detection in surveillance video, and large-scale video search enabled by advances in computer vision techniques.
The document discusses improving 3D scene understanding from images by incorporating stronger geometric constraints and reasoning. It suggests moving from qualitative, low-level representations to more quantitative representations that model precise boundaries, interposition, and depth ordering. This could allow combining reasoning about both geometric relations and semantic labels. Several challenges are noted, such as how to generate and search the large hypothesis space in a tractable way while avoiding early decisions, and how to represent constraints in a general way. Overall, the goal is to develop techniques that achieve true integration of geometric and semantic cues for scene interpretation.
Devoxx france 2014 - Outils du manager - Youen ChénéSaagie
Vous avez tous connu des bons ou (plus souvent) des mauvais managers dans votre carrière. Au gré de la croissance de votre société, de réorganisations ou de rachats, il arrive pour de bonnes ou de mauvaises raisons que vous-même teniez un rôle de management. Un rôle pas forcément à l'honneur dans notre communauté.
Le management, comme le développement, se base aussi sur des pratiques et des techniques. Voici une revue d'outils pragmatique et simple à mettre en place pour vous améliorer dans votre (nouveau) role de manager.
This document summarizes key concepts from CS 221 lecture 5 on hidden Markov models and temporal filtering. The lecture covered Markov chains, hidden Markov models, and particle filtering for approximate inference in hidden Markov models. Hidden Markov models extend Markov chains to allow for hidden states that are observed indirectly through emissions. Particle filtering uses samples or "particles" to represent the distribution over hidden states and approximate inference.
ECCV2010: feature learning for image classification, part 3zukun
The document discusses sparse coding techniques for image classification. It introduces two views of sparse coding - the topic model view where each basis represents a topic, and the geometric view where bases represent anchor points on a data manifold. A theoretical framework called local coordinate coding connects coding to nonlinear function learning. The document also describes practical coding methods like locality-constrained linear coding and super-vector coding, and their application to improving bag-of-words models for image classification.
The document discusses several topics related to computer vision and object recognition. It begins by questioning what would happen if object recognition and segmentation were solved. It notes that this would only solve a small part of scene understanding, as images tell complex stories similar to written language. It then discusses how to give effective presentations, including preparing, delivering talks with confidence while acknowledging limitations, and practicing. It concludes by providing an agenda for the next class meeting covering several papers on topics like scene understanding, object detection, and sketch recognition.
This document introduces visualization and summarizes three key libraries for scientific visualization - VTK, TVTK, and MayaVi2. It provides an overview of each library and examples of creating 3D visualizations with TVTK's visual and mlab tools, including visualizing spheres, boxes, animating a bouncing ball, and plotting curves in 3D space. The document is intended as an introduction for scientists and engineers to get started with 3D data visualization.
Principal component analysis and matrix factorizations for learning (part 1) ...zukun
This document discusses principal component analysis (PCA) and matrix factorizations for learning. It provides an overview of PCA and singular value decomposition (SVD), their history and applications. PCA and SVD are widely used techniques for dimensionality reduction and data transformation. The document also discusses how PCA relates to other methods like spectral clustering and correspondence analysis.
MEDIAPOST, leader en France de la communication de proximiteMEDIAPOST
MEDIAPOST, expert du Marketing Relationnel et de la communication ciblee en boite aux lettres.
MEDIAPOST, un acteur de terrain ancré dans la proximité, une entreprise en prise directe avec son environnement, des engagements forts pour le développement responsable.
Présentation de nos solutions digitales à la performance pour aider les e-commercants à générer du trafic, collecter des leads et augmenter leur conversion.
Nos leviers :
Display à la performance / RTB / Programmatique
Influence marketing
E-mailing marketing
Retargeting performance
Affiliation marketing
Lead Generation
Presentation Appiscreen, régie pub vidéo mobile et agence marketing vidéo mobileStephane Boulissiere
Appiscreen est un ad network vidéo mobile & agence marketing vidéo mobile, tout en un.
Nous réalisons des campagnes publicitaires vidéo sur mobile, tablette en interstitiel sur un inventaire d’applications mobiles identifiées et segmentées.
L’offre est vraiment dans l'ère, nouvelle, quasi-exclusive en France et permet de faire et du branding et de la performance.
Nous réalisons aussi les interstitiels vidéo comme une agence si besoin, compris dans le prix de la campagne.
Des exemples peuvent être visualisés dans la présentation en PJ.
Nous pouvons aussi cibler les campagnes en fonction de l’audience recherchée, ajouter de l’interactivité avec l’utilisateur (drive to store, call to action, téléchargement d’application, leads…).
Le DSP Appiscreen (Demand Side Platform) est notre nouvelle plateforme en ligne permettant aux annonceurs et agences médias de centraliser le pilotage de leurs campagnes mobile dans une même interface. Il est la pierre angulaire des campagnes mobiles en 2015 pour les agences, annonceurs & trading desk.
Quel est le bénéfice du RTB pour vos campagnes mobiles ?
Avec notre technologie, il est très simple d’acheter des impressions et des clics sur des sites et application mobiles, en temps réel.
En tenant compte de multiples paramètres de ciblage, le RTB permet d'optimiser vos dépenses, vous permettant d'enchérir uniquement sur les impressions qui répondent vos besoins en utilisant des techniques de ciblage d'achat programmatiques.
La plateforme DSP Appiscreen et le RTA
Le DSP Appiscreen ouvre une toute nouvelle dimension du marketing mobile avec une technologie de publicité en temps réel (RTA - Real Time Advertising) basée sur des algorithmes élaborés et inédits qui vous permettent d’avoir un maximum de résultats avec l'achat programmatique.
En quelques secondes, vos campagnes publicitaires mobiles peuvent être affichées au coût par impression (CPM), coût par clic (CPC) avec une option (CPA). La plate-forme vous permet de cibler les sites mobiles et applications individuellement, vous donnant le contrôle total au niveau de votre campagne.
Partenaires
Appiscreen est intégré avec une douzaine plateforme de Real-Time Advertising (RTA)
Soit 7 millions d’applications et sites pour 12 milliards d’impressions par jour
Formats Publicitaires
Appiscreen est expert de la publicité mobile Rich média et vidéo. Notre studio intégré vous accompagne et réalise les formats publicitaires les performants et créatifs.
Analyse et rapports complets
Notre interface de d’analyse détaillée vous donne un aperçu complet sur les performances de la campagne permettant de maximiser le retour sur investissement.
Interface simple d’utilisation, Accès à un inventaire mondial dans 135 pays, Plateforme en self-service, Analyse et rapports en temps réel, Transparence des publishers
Options de ciblages
Lieux, Systèmes d’exploitation, Operateurs/WI-FI, Sites, URL, Heures de publication, Capping par utilisateur, Audiences recherchés, Thématique, Langues, Nom de l’application, Appareils
L'Offre BUSMEDIA, Affichage et Événementiel sur Bus
Affichage sur Bus à Marrakech, Agadir et Tanger.
Bus panoramique à deux étages pour vos opérations dans tout le Maroc.
Muse Motivation, l'agence des acteurs de la venteMuse
Muse est l’agence des acteurs de la vente du groupe Loyalty Company.
L’agence propose une palette de solutions originales et efficaces pour embarquer et engager les acteurs de la vente. De l’accompagnement conseil aux dotations, en passant par la plateforme digitale d’animation, l’agence cherche à booster la performance de vos opérations de motivation, fidélisation et promotion des ventes.
Dirigée par Stéphanie Noyers, l’agence compte 20 collaborateurs et se classe parmi les leaders des agences de motivation & récompenses, avec un chiffre d’affaires de 13 M €.
www.muse-motivation.fr
Spécialisée dans l’ingénierie informatique, White Bay Limited est née d’un partenariat public-privé formant une synergie de compétences jeunes et dynamiques, alliées à l’expérience et l’expertise de l’Agence Nationale de Développement des Parcs Technologiques (EPIC ANPT). WBL se donne comme mission d’accompagner les entreprises dans leur transformation digitale et ceci à trois niveau : Le diagnostic, le développement et la mise en place de solutions numériques capable d’optimiser leurs performances. White Bay Limited dispose d’équipes de professionnelles travaillant de manière agiles et aptes à prendre en charge tous types de projets numériques. White Bay Limited dispose également de progiciels développés en interne dans le domaine de la logistique, la géolocalisation et le CRM.
Pour en savoir plus : whitebay.limited
Natp.dz
#it #Transformationdigitale #CRM #Solutionsmart #DigitalMarketing
CONFERENCE – Fidélisation, relation client et innovation marketingClubCommerceConnecte
Le Club Commerce Connecté a organisé une soirée-conférence le jeudi 13 février l’ISG Bordeaux. La soirée était consacrée à la thématique "fidélisation, relation client et innovation marketing". Au programme :
- Dolist a dévoilé, avec App's Miles les clés d’une fidélisation réussie,
- JouéClub a présenté les dernières innovations marketing de l’enseigne,
- Mirane a montré comment les innovations marketing influent sur les relations clients.
Comme toujours, un moment convivial pour poursuivre les échanges a été prévu.
AMPLEXOR Digital Experience tend à créer des expériences exceptionnelles à travers les points de contact digitaux de votre entreprise. En partenariat avec les éditeurs leaders du marché, nous planifions, concevons et mettons en oeuvre des stratégies sur mesure pour accompagner la présence et les initiatives digitales de votre entreprise.
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Les véhicules publicitaires de Pub Pro-Média émettent
moins d’émissions de CO2 lors des trajets, n’émettent
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