Isbn: 9781032557496 - computer vision: object detection in adversarial vision (18 risultati)

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2025

    1032557494 / 9781032557496

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  • Lingua: Inglese

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  • Lingua: Inglese

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  • Lingua: Inglese

    Editore: Taylor & Francis Ltd, 2025

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2025

    1032557494 / 9781032557496

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2025

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  • Lingua: Inglese

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  • Lingua: Inglese

    Editore: Taylor & Francis Ltd, 2025

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    Paperback. Condizione: Brand New. 208 pages. 9.18x6.12x9.21 inches. In Stock.

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd, 2025

    1032557494 / 9781032557496

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    Paperback. Condizione: new. Paperback. This comprehensive textbook presents a broad review of both traditional (i.e., conventional) and deep learning aspects of object detection in various adversarial real-world conditions in a clear, insightful, and highly comprehensive style. Beginning with the relation of computer vision and object detection, the text covers the various representation ofobjects, applications of object detection, and real-world challenges faced by the research community for object detection task. The book addresses various real-world degradations and artifacts for the object detection task and also highlights the impacts of artifacts in the object detection problems. The book covers various imaging modalities and benchmark datasets mostly adopted by the research community for solving various aspects of object detection tasks. The book also collects together solutions and perspectives proposed by the preeminent researchers in the field, addressing not only the background of visibility enhancement but also techniques proposed in the literature for visibility enhancement of scenes and detection of objects in various representative real-world challenges.Computer Vision: Object Detection in Adversarial Vision is unique for its diverse content, clear presentation, and overall completeness. It provides a clear, practical, and detailed introduction and advancement of object detection in various representative challenging real-world conditions.Topics and Features: Offers the first truly comprehensive presentation of aspects of the object detection in degraded and nondegraded environment. Includes in-depth discussion of various degradation and artifacts, and impact of those artifacts in the real world on solving the object detection problems. Gives detailed visual examples of applications of object detection in the real world. Presents a detailed description of popular imaging modalities for object detection adopted by researchers. Presents the key characteristics of various benchmark datasets in indoor and outdoor environment for solving object detection tasks. Surveys the complete field of visibility enhancement of degraded scenes, including conventional methods designed for enhancing the degraded scenes as well as the deep architectures. Discusses techniques for detection of objects in real-world applications. Contains various hands-on practical examples and a tutorial for solving object detection problems using Python. Motivates readers to build vision-based systems for solving object detection problems in degraded and nondegraded real-world challenges.The book will be of great interest to a broad audience ranging from researchers and practitioners to graduate and postgraduate students involved in computer vision tasks with respect to object detection in degraded and nondegraded real-world vision problems. This comprehensive text/ book presents a broad review of both traditional (i.e., conventional) and the deep learning aspects of object detection in various adversarial conditions of real-world in a clear, insightful, and highly comprehensive style. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd, 2025

    1032557494 / 9781032557496

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    Paperback. Condizione: new. Paperback. This comprehensive textbook presents a broad review of both traditional (i.e., conventional) and deep learning aspects of object detection in various adversarial real-world conditions in a clear, insightful, and highly comprehensive style. Beginning with the relation of computer vision and object detection, the text covers the various representation ofobjects, applications of object detection, and real-world challenges faced by the research community for object detection task. The book addresses various real-world degradations and artifacts for the object detection task and also highlights the impacts of artifacts in the object detection problems. The book covers various imaging modalities and benchmark datasets mostly adopted by the research community for solving various aspects of object detection tasks. The book also collects together solutions and perspectives proposed by the preeminent researchers in the field, addressing not only the background of visibility enhancement but also techniques proposed in the literature for visibility enhancement of scenes and detection of objects in various representative real-world challenges.Computer Vision: Object Detection in Adversarial Vision is unique for its diverse content, clear presentation, and overall completeness. It provides a clear, practical, and detailed introduction and advancement of object detection in various representative challenging real-world conditions.Topics and Features: Offers the first truly comprehensive presentation of aspects of the object detection in degraded and nondegraded environment. Includes in-depth discussion of various degradation and artifacts, and impact of those artifacts in the real world on solving the object detection problems. Gives detailed visual examples of applications of object detection in the real world. Presents a detailed description of popular imaging modalities for object detection adopted by researchers. Presents the key characteristics of various benchmark datasets in indoor and outdoor environment for solving object detection tasks. Surveys the complete field of visibility enhancement of degraded scenes, including conventional methods designed for enhancing the degraded scenes as well as the deep architectures. Discusses techniques for detection of objects in real-world applications. Contains various hands-on practical examples and a tutorial for solving object detection problems using Python. Motivates readers to build vision-based systems for solving object detection problems in degraded and nondegraded real-world challenges.The book will be of great interest to a broad audience ranging from researchers and practitioners to graduate and postgraduate students involved in computer vision tasks with respect to object detection in degraded and nondegraded real-world vision problems. This comprehensive text/ book presents a broad review of both traditional (i.e., conventional) and the deep learning aspects of object detection in various adversarial conditions of real-world in a clear, insightful, and highly comprehensive style. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd, 2025

    1032557494 / 9781032557496

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    Paperback. Condizione: new. Paperback. This comprehensive textbook presents a broad review of both traditional (i.e., conventional) and deep learning aspects of object detection in various adversarial real-world conditions in a clear, insightful, and highly comprehensive style. Beginning with the relation of computer vision and object detection, the text covers the various representation ofobjects, applications of object detection, and real-world challenges faced by the research community for object detection task. The book addresses various real-world degradations and artifacts for the object detection task and also highlights the impacts of artifacts in the object detection problems. The book covers various imaging modalities and benchmark datasets mostly adopted by the research community for solving various aspects of object detection tasks. The book also collects together solutions and perspectives proposed by the preeminent researchers in the field, addressing not only the background of visibility enhancement but also techniques proposed in the literature for visibility enhancement of scenes and detection of objects in various representative real-world challenges.Computer Vision: Object Detection in Adversarial Vision is unique for its diverse content, clear presentation, and overall completeness. It provides a clear, practical, and detailed introduction and advancement of object detection in various representative challenging real-world conditions.Topics and Features: Offers the first truly comprehensive presentation of aspects of the object detection in degraded and nondegraded environment. Includes in-depth discussion of various degradation and artifacts, and impact of those artifacts in the real world on solving the object detection problems. Gives detailed visual examples of applications of object detection in the real world. Presents a detailed description of popular imaging modalities for object detection adopted by researchers. Presents the key characteristics of various benchmark datasets in indoor and outdoor environment for solving object detection tasks. Surveys the complete field of visibility enhancement of degraded scenes, including conventional methods designed for enhancing the degraded scenes as well as the deep architectures. Discusses techniques for detection of objects in real-world applications. Contains various hands-on practical examples and a tutorial for solving object detection problems using Python. Motivates readers to build vision-based systems for solving object detection problems in degraded and nondegraded real-world challenges.The book will be of great interest to a broad audience ranging from researchers and practitioners to graduate and postgraduate students involved in computer vision tasks with respect to object detection in degraded and nondegraded real-world vision problems. This comprehensive text/ book presents a broad review of both traditional (i.e., conventional) and the deep learning aspects of object detection in various adversarial conditions of real-world in a clear, insightful, and highly comprehensive style. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

  • Lingua: Inglese

    Editore: CRC Press, 2025

    1032557494 / 9781032557496

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Mrinal Kanti Bhowmik earned a Bachelor of Engineering (BE) degree in Computer Science and Engineering from the Tripura Engineering College, Government of Tripura, in 2004, a Master of Technology (M.Tech) degree in Computer Science and En.

  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2025

    1032557494 / 9781032557496

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    Taschenbuch. Condizione: Neu. Computer Vision | Object Detection In Adversarial Vision | Mrinal Kanti Bhowmik | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2025 | Chapman and Hall/CRC | EAN 9781032557496 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

  • Lingua: Inglese

    Editore: Chapman And Hall/CRC, 2025

    1032557494 / 9781032557496

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    Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This comprehensive text/ book presents a broad review of both traditional (i.e., conventional) and the deep learning aspects of object detection in various adversarial conditions of real-world in a clear, insightful, and highly comprehensive style.