Computational Models Cognitive Vision by Ghosh Hiranmay (24 results)

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Paperback. Condition: New. Learn how to apply cognitive principles  to the problems of computer vision  Computational Models for Cognitive Vision formulates the computational models for the cognitive principles found in biological vision,  and applies those models to computer vision tasks. Such principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to name a few. The author's ultimate goal is to provide a framework for creation of a machine vision system  with the capability and versatility of the human vision.   Written by Dr. Hiranmay Ghosh, the book takes readers through the basic principles and the computational models for cognitive vision, Bayesian reasoning for perception and cognition, and other related topics, before establishing the relationship of cognitive vision with the multi-disciplinary field broadly referred to as "artificial intelligence". The principles are illustrated with diverse application examples in computer vision, such as computational photography, digital heritage and social robots. The author concludes with suggestions for future research and salient observations about the state of the field of cognitive vision.  Other topics covered in the book include:  ·         knowledge representation techniques  ·         evolution of cognitive architectures  ·         deep learning approaches for visual cognition    Undergraduate students, graduate students, engineers, and researchers interested in cognitive vision will consider this an indispensable and practical resource in the development and study of computer vision.

Paperback. Condition: new. Paperback. Learn how to apply cognitive principles to the problems of computer vision Computational Models for Cognitive Vision formulates the computational models for the cognitive principles found in biological vision, and applies those models to computer vision tasks. Such principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to name a few. The authors ultimate goal is to provide a framework for creation of a machine vision system with the capability and versatility of the human vision. Written by Dr. Hiranmay Ghosh, the book takes readers through the basic principles and the computational models for cognitive vision, Bayesian reasoning for perception and cognition, and other related topics, before establishing the relationship of cognitive vision with the multi-disciplinary field broadly referred to as artificial intelligence. The principles are illustrated with diverse application examples in computer vision, such as computational photography, digital heritage and social robots. The author concludes with suggestions for future research and salient observations about the state of the field of cognitive vision. Other topics covered in the book include: knowledge representation techniques evolution of cognitive architectures deep learning approaches for visual cognition Undergraduate students, graduate students, engineers, and researchers interested in cognitive vision will consider this an indispensable and practical resource in the development and study of computer vision. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Paperback. Condition: new. Paperback. Learn how to apply cognitive principles to the problems of computer vision Computational Models for Cognitive Vision formulates the computational models for the cognitive principles found in biological vision, and applies those models to computer vision tasks. Such principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to name a few. The authors ultimate goal is to provide a framework for creation of a machine vision system with the capability and versatility of the human vision. Written by Dr. Hiranmay Ghosh, the book takes readers through the basic principles and the computational models for cognitive vision, Bayesian reasoning for perception and cognition, and other related topics, before establishing the relationship of cognitive vision with the multi-disciplinary field broadly referred to as artificial intelligence. The principles are illustrated with diverse application examples in computer vision, such as computational photography, digital heritage and social robots. The author concludes with suggestions for future research and salient observations about the state of the field of cognitive vision. Other topics covered in the book include: knowledge representation techniques evolution of cognitive architectures deep learning approaches for visual cognition Undergraduate students, graduate students, engineers, and researchers interested in cognitive vision will consider this an indispensable and practical resource in the development and study of computer vision. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Paperback. Condition: new. Paperback. Learn how to apply cognitive principles to the problems of computer vision Computational Models for Cognitive Vision formulates the computational models for the cognitive principles found in biological vision, and applies those models to computer vision tasks. Such principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to name a few. The authors ultimate goal is to provide a framework for creation of a machine vision system with the capability and versatility of the human vision. Written by Dr. Hiranmay Ghosh, the book takes readers through the basic principles and the computational models for cognitive vision, Bayesian reasoning for perception and cognition, and other related topics, before establishing the relationship of cognitive vision with the multi-disciplinary field broadly referred to as artificial intelligence. The principles are illustrated with diverse application examples in computer vision, such as computational photography, digital heritage and social robots. The author concludes with suggestions for future research and salient observations about the state of the field of cognitive vision. Other topics covered in the book include: knowledge representation techniques evolution of cognitive architectures deep learning approaches for visual cognition Undergraduate students, graduate students, engineers, and researchers interested in cognitive vision will consider this an indispensable and practical resource in the development and study of computer vision. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Paperback. Condition: New. Learn how to apply cognitive principles  to the problems of computer vision  Computational Models for Cognitive Vision formulates the computational models for the cognitive principles found in biological vision,  and applies those models to computer vision tasks. Such principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to name a few. The author's ultimate goal is to provide a framework for creation of a machine vision system  with the capability and versatility of the human vision.   Written by Dr. Hiranmay Ghosh, the book takes readers through the basic principles and the computational models for cognitive vision, Bayesian reasoning for perception and cognition, and other related topics, before establishing the relationship of cognitive vision with the multi-disciplinary field broadly referred to as "artificial intelligence". The principles are illustrated with diverse application examples in computer vision, such as computational photography, digital heritage and social robots. The author concludes with suggestions for future research and salient observations about the state of the field of cognitive vision.  Other topics covered in the book include:  ·         knowledge representation techniques  ·         evolution of cognitive architectures  ·         deep learning approaches for visual cognition    Undergraduate students, graduate students, engineers, and researchers interested in cognitive vision will consider this an indispensable and practical resource in the development and study of computer vision.

Taschenbuch. Condition: Neu. Neuware - Learn how to apply cognitive principles to the problems of computer visionComputational Models for Cognitive Vision formulates the computational models for the cognitive principles found in biological vision, and applies those models to computer vision tasks. Such principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to name a few. The author's ultimate goal is to provide a framework for creation of a machine vision system with the capability and versatility of the human vision.Written by Dr. Hiranmay Ghosh, the book takes readers through the basic principles and the computational models for cognitive vision, Bayesian reasoning for perception and cognition, and other related topics, before establishing the relationship of cognitive vision with the multi-disciplinary field broadly referred to as 'artificial intelligence'. The principles are illustrated with diverse application examples in computer vision, such as computational photography, digital heritage and social robots. The author concludes with suggestions for future research and salient observations about the state of the field of cognitive vision.Other topics covered in the book include:\* knowledge representation techniques\* evolution of cognitive architectures\* deep learning approaches for visual cognitionUndergraduate students, graduate students, engineers, and researchers interested in cognitive vision will consider this an indispensable and practical resource in the development and study of computer vision.

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Paperback. Condition: Brand New. 120 pages. 8.75x6.00x0.50 inches. In Stock. This item is printed on demand.