Advances in Computer Vision and Pattern Sparse Representation Modeling and Learning in Visual Recognition: Theory Algorithms and Applications Paperback from other stores
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Advances in Computer Vision an...
This unique text/reference presents a comprehensive review of the state of the...
This unique text/reference presents a comprehensive review of the state of the art in sparse representations modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation highlighting the practical...
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Advances in Computer Vision an...
This unique text/reference presents a comprehensive review of the state of the...
This unique text/reference presents a comprehensive review of the state of the art in sparse representations modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation highlighting the practical...
more
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Pre-Owned Advances in Computer...
This unique text/reference presents a comprehensive review of the state of the...
This unique text/reference presents a comprehensive review of the state of the art in sparse representations modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation highlighting the practical...
more
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Computer Vision and Pattern Re...
Deep Learning through Sparse Representation and Low-Rank Modeling bridges clas...
Deep Learning through Sparse Representation and Low-Rank Modeling bridges classical sparse and low rank models--those that emphasize problem-specific Interpretability--with recent deep network models that have enabled a larger learning capacity and...
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Advances in Computer Vision an...
This book surveys the state of the art in multidimensional physically-correct ...
This book surveys the state of the art in multidimensional physically-correct visual texture modeling. Features: reviews the entire process of texture synthesis including material appearance representation measurement analysis compression modeling...
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Pre-Owned Advances in Computer...
This thoroughly revised and expanded new edition now includes a more detailed ...
This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm a description of an efficient approximate Viterbi-training procedure a theoretical derivation of the perplexity measure and coverage of...
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Pre-Owned Advances in Computer...
This thoroughly revised and expanded new edition now includes a more detailed ...
This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm a description of an efficient approximate Viterbi-training procedure a theoretical derivation of the perplexity measure and coverage of...
more
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Pre-Owned Advances in Computer...
This book reviews the state of the art in algorithmic approaches addressing th...
This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks with a focus on emerging trends in machine learning and image processing/understanding. It...
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Pre-Owned Advances in Computer...
Markov random field (MRF) theory provides a basis for modeling contextual cons...
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms systematically when used with optimization principles. This book...
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Advances in Computer Vision an...
This thoroughly revised and expanded new edition now includes a more detailed ...
This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm a description of an efficient approximate Viterbi-training procedure a theoretical derivation of the perplexity measure and coverage of...
more
-
Advances in Computer Vision an...
This thoroughly revised and expanded new edition now includes a more detailed ...
This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm a description of an efficient approximate Viterbi-training procedure a theoretical derivation of the perplexity measure and coverage of...
more
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Advances in Computer Vision an...
Techniques of vision-based motion analysis aim to detect track identify and ge...
Techniques of vision-based motion analysis aim to detect track identify and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human-machine...
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Advances in Computer Vision an...
Techniques of vision-based motion analysis aim to detect track identify and ge...
Techniques of vision-based motion analysis aim to detect track identify and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human-machine...
more
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Pre-Owned Advances in Computer...
Principles of Visual Information Retrieval introduces the basic concepts and t...
Principles of Visual Information Retrieval introduces the basic concepts and techniques in VIR and develops a foundation that can be used for further research and study. Divided into 2 parts the first part describes the fundamental principles. A...
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Pre-Owned Advances in Computer...
This book reviews the state of the art in deep learning approaches to high-per...
This book reviews the state of the art in deep learning approaches to high-performance robust disease detection robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities) and the construction...
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