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Condition: New. pp. XI, 461 177 illus., 156 illus. in color. 1st ed. 2019 edition NO-PA16APR2015-KAP.
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Taschenbuch. Condition: Neu. Advances in Gait-Based Identification | A Systematic Review of Deep Learning Models Leveraging Computer Vision Techniques | Diogo R. M. Bastos (u. a.) | Taschenbuch | Studies in Systems, Decision and Control | Englisch | 2026 | Springer | EAN 9783031895623 | Verantwortliche Person für die EU: Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg, productsafety[at]springernature[dot]com | Anbieter: preigu.
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ISBN 10: 3031895592 ISBN 13: 9783031895593
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a systematic review of gait-based person identification, categorizing studies into deep-learning and non-deep-learning approaches while analyzing key datasets and performance metrics. It explores challenges such as covariant factors, e.g., viewing angles, clothing, and accessories, and highlights advancements in real-world gait recognition systems. With a structured methodology and transparent review process, this work serves as a valuable reference for researchers and a foundation for future developments in biometric identification.
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a systematic review of gait-based person identification, categorizing studies into deep-learning and non-deep-learning approaches while analyzing key datasets and performance metrics. It explores challenges such as covariant factors, e.g., viewing angles, clothing, and accessories, and highlights advancements in real-world gait recognition systems. With a structured methodology and transparent review process, this work serves as a valuable reference for researchers and a foundation for future developments in biometric identification.
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