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Image processing in machine vision is a challenging task because often real-time requirements have to be met in these systems. To accelerate the processing tasks in machine vision and to reduce data transfer latencies, new architectures for embedded systems in intelligent cameras are required. Furthermore, innovative processing approaches are necessary to realize these architectures efficiently. Marching Pixels are such a processing scheme, based on Organic Computing principles, and can be applied for example to determine object centroids in binary or gray-scale images. In this paper, we present a processing pipeline for smart camera systems utilizing such Marching Pixel algorithms. It consists of a buffering template for image pre-processing tasks in a FPGA to enhance captured images and an ASIC for the efficient realization of Marching Pixel approaches. The ASIC achieves a speedup of eight for the realization of Marching Pixel algorithms, compared to a common medium performance DSP platform.

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: In this Paper, A novel architecture for automotive vision using an embedded device will be implemented on ARM9 Board with highly computing capabilities and low processing power. Currently, achieving real-time image processing routines such as convolution, thresholding, edge detection and some of the complex media applications is a challenging task in embedded Device, because of limited memory. An open software framework, Linux OS is used in embedded devices to provide a good starting point for developing the multitasking kernel, integrated with communication protocols, data management and graphical user interface for reducing the total development time. To resolve the problems faced by the image processing applications in embedded Device a new application environment was developed. This environment provides the resources available in the operating system which runs on the hardware with complex image processing libraries. This paper presents the capture of an image from the USB camera, applied to image processing algorithms to Detect Human Upper Body. The application (GUI) Graphical User Interface was designed using Qt and ARM Linux gcc Integrated Development Environment (IDE) for implementing image processing algorithm using Open Source Computer Vision Library (OpenCV). This developed software integrated in mobiles by the cross compilation of Qt and the OpenCV software for Linux Operating system. The result utilized by Viola and Jones Algorithm with Haar Features of the image using OpenCV.

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Deep learning continues to push the state of the art in domains such as video analytics, computer vision, and speech recognition. Deep networks are powered by amazing levels of representational power, feature learning, and abstraction. This approach comes at the cost of a significant increase in required compute power, which makes the AWS cloud an excellent environment for training. Innovators in this space are applying deep learning to a variety of applications. One such innovator, Vilynx, a startup based in Palo Alto, realized that the current pre-roll advertising-based models for mobile video weren’t returning publishers' desired levels of engagement. In this session, we explain the algorithmic challenges of scaling across multiple nodes, and what Intel is doing on AWS to overcome them. We describe the benefits of using AWS CloudFormation to set up a distributed training environment for deep networks. We also showcase Vilynx’s contributions to video discoverability, and explain how Vilynx uses AWS tools to understand video content. This session is sponsored by Intel.

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Automatic License Plate Recognition system is a real time embedded system which automatically recognizes the license plate of vehicles. There are many applications ranging from complex security systems to common areas and from parking admission to urban traffic control. Automatic license plate recognition (ALPR) has complex characteristics due to diverse effects such as of light and speed. Most of the ALPR systems are built using proprietary tools like Matlab. This paper presents an alternative method of implementing ALPR systems using Free Software including Python and the Open Computer Vision Library.

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The expanding demand for imaging- and vision-based systems in mobile, IoT and automotive products is making the need for multi camera and sensor fusion systems look for novel ways to gather and process multiple data streams while still fitting into the mobile interface. The CSI-2 protocol allows camera sensor and processed image data to be combined into a single data stream using interleaving, allowing the application processor to extract the image data using the virtual channel or data type information. In this presentation, Richard Sproul of Cadence Design Systems will highlight some of the key details and requirements for a system with image processing of multi camera/sensor systems.

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The current paper is mainly about maintaining a secure environment and also free from thefts that are happening in our home. The present paper discusses about the detection of intruders with the help of the various devices and software.. OpenCV(open source computer vision) is the major software that is being used in our present work. For detecting faces we are using various algorithms like Haar cascade, linear SVM, deep neural network etc. The main method that we have proposed in our work is, if any person comes in front of the pi camera, first it will look for potential matches that we have already stored in our system If the module finds a match then it continues to record until any intruder comes. If the face is not recognized then the unknown person’s face will be captured and a snap shot will be sent to the user’s email. The device is developed using Raspberry Pi b+ with 1.4 GHz quad core processor, raspberry pi camera module and a Wireless dongle to communicate with user’s email. OpenCV, Rassberry pi, python

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I'm excited to share my latest predictions on how AI, robotics, and other technological advancements will reshape industries in the coming years. The slides explore the exponential growth of computational power, the future of AI and robotics, and their profound impact on various sectors. Why this matters: The success of new products and investments hinges on precise timing and foresight into emerging categories. This deck equips founders, VCs, and industry leaders with insights to align future products with upcoming tech developments. These insights enhance the ability to forecast industry trends, improve market timing, and predict competitor actions. Highlights: ▪ Exponential Growth in Compute: How $1000 will soon buy the computational power of a human brain ▪ Scaling of AI Models: The journey towards beyond human-scale models and intelligent edge computing ▪ Transformative Technologies: From advanced robotics and brain interfaces to automated healthcare and beyond ▪ Future of Work: How automation will redefine jobs and economic structures by 2040 With so many predictions presented here, some will inevitably be wrong or mistimed, especially with potential external disruptions. For instance, a conflict in Taiwan could severely impact global semiconductor production, affecting compute costs and related advancements. Nonetheless, these slides are intended to guide intuition on future technological trends.

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This presentation focuses on the challenges and strategies of connecting problem definitions within product development. Key Points Covered: - Kayak's mission since its inception in 2004 to simplify travel by enabling easy comparisons of flights through technological solutions. - Discussion of the complexities within the travel industry, including the high expectations for personalized user experiences and the various stakeholder influences. - Emphasis on the necessity of maintaining agility and innovation within a mature company through continuous reassessment of processes. - An explanation of the importance of disciplined problem definition to prevent project failures and team inefficiencies. - Introduction of strategies for effective communication across teams to ensure alignment and comprehension at all levels of project development. - Exploration of various problem-solving methodologies, including how to handle conflicts within team settings regarding problem definitions and project directions.

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The Epson EcoTank L3210 is a high-performance and cost-efficient printer designed to meet the printing needs of both home users and small businesses. Equipped with Epson’s revolutionary EcoTank ink tank system, the Epson eliminates the need for traditional ink cartridges, thereby significantly reducing printing costs and plastic waste. With its PrecisionCore technology, this printer delivers sharp, vibrant prints for both documents and photos. Its user-friendly design ensures easy setup and operation, while its compact form factor saves valuable desk space. Whether it’s everyday printing jobs or creative projects, the Epson EcoTank L3210 provides a reliable and eco-friendly printing solution.

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