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Sinopsis
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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Acerca del autor
Diogo R. M. Bastos holds an MSc in biomedical engineering from the Faculdade de Engenharia da Universidade do Porto (FEUP). His research interests include artificial intelligence, computer vision, and gait-based biometric identification.
João Manuel R. S. Tavares is a Full Professor in the Department of Mechanical Engineering at the Faculdade de Engenharia da Universidade do Porto (FEUP) and a senior researcher at the Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial (INEGI). His research focuses on computational vision, medical imaging, biomechanics, and biomedical engineering.
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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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Advances in Gait-Based Identification (eng)
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Advances in Gait-Based Identification (Hardcover)
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Hardcover. Condición: new. Hardcover. 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Nº de ref. del artículo: 9783031895593
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Advances in Gait-Based Identification
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 96 pp. Englisch. Nº de ref. del artículo: 9783031895593
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Advances in Gait-Based Identification : A Systematic Review of Deep Learning Models Leveraging Computer Vision Techniques
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Buch. Condición: 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. Nº de ref. del artículo: 9783031895593
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Advances in Gait-Based Identification: A Systematic Review of Deep Learning Models Leveraging Computer Vision Techniques (Studies in Systems, Decision and Control, 593)
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Advances in Gait-Based Identification
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Advances in Gait-Based Identification (Hardcover)
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Hardcover. Condición: new. Hardcover. 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. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9783031895593
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Advances in Gait-Based Identification: A Systematic Review of Deep Learning Models Leveraging Computer Vision Techniques (Studies in Systems, Decision and Control, 593)
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Advances in Gait-Based Identification: A Systematic Review of Deep Learning Models Leveraging Computer Vision Techniques (Studies in Systems, Decision and Control, 593)
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Advances in Gait-Based Identification: A Systematic Review of Deep Learning Models Leveraging Computer Vision Techniques (Studies in Systems, Decision and Control, 593)
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