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In the field of image processing, many applications require real-time execution, particularly those in the domains of medicine, robotics;
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An invaluable source for both imaging and software engineers, this practical guide thoroughly covers information in real-time systems;
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The book covers the most crucial parts of real-time hyperspectral image processing: causality and real-time capability. Recently, two new;
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environment into a real-time constrained environment. Such guidelines and strategies are scattered in the literature of various disciplines including;
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This book covers recent advances in image processing and imaging sciences from an optimization viewpoint, especially convex optimization;
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processing, focusing on nature-inspired algorithms that are linked with deep learning, such as ant colony optimization, particle swarm optimization;
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geometry algorithms, data allocation strategies for parallel image processing algorithms, complexity analysis of parallel image operators. The;
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Real-world problems and modern optimization techniques to solve them Here, a team of international experts brings together core ideas for;
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networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you'll explore how models are made in real;
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networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later yoüll explore how models are made in real;
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medical field using various medical image processing techniques. The book discusses real-time applications for artificial intelligence and machine;
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theoretical models; image pre-processing; automatic target detection, recognition and tracking; and embedded real-time processing systems. The book;
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theoretical models; image pre-processing; automatic target detection, recognition and tracking; and embedded real-time processing systems. The book;
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This book presents practical optimization techniques used in image processing and computer vision problems. Ill-posed problems are;
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: image enhancement and optimization, image restoration, and image compression.;
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This book describes the optimization methods most commonly encountered in signal and image processing: artificial evolution and Parisian;
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. In particular, recent work has explored broader application to the design, optimization, and simulation of computer architecture. Notably, machine;
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Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures;
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of the best algorithms, and demonstrates those algorithms with real-world applications from many fields. It covers all aspects of image;
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) technologies, examining methods and algorithms for image analysis, optimization, segmentation, and restoration. It focuses on recent approaches and;
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recipes dealing with webcams and various video streams, giving you ready-made code with which to do real-time video analysis. What You Will;
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This book presents the use of efficient Evolutionary Computation (EC) algorithms for solving diverse real-world image processing and;
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This book presents the use of efficient Evolutionary Computation (EC) algorithms for solving diverse real-world image processing and;
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experts, Image Sensors and Image Processing for Digital Still Cameras offers unparalleled real-world coverage and opens wide the door for future;
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the most experienced and published authors in the field. This includes a range of processes from optimization strategies for improving the;
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; compressed sensing, sparse coding; social computing; neural networks; nature inspired computing and optimization; genetic algorithms; signal;
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; compressed sensing, sparse coding; social computing; neural networks; nature inspired computing and optimization; genetic algorithms; signal;
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