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Computer vision. --- Information visualization. --- Data visualization --- Visualization of information --- Information science --- Visual analytics --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems
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Computer and Machine Vision: Theory, Algorithms, Practicalities (previously entitled Machine Vision) clearly and systematically presents the basic methodology of computer and machine vision, covering the essential elements of the theory while emphasizing algorithmic and practical design constraints. This fully revised fourth edition has brought in more of the concepts and applications of computer vision, making it a very comprehensive and up-to-date tutorial text suitable for graduate students, researchers and R&D engineers working in this vibrant subject. Key features include: <
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"Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 5-10 years. The book provides clear explanations of principles and algorithms supported with applications. Topics covered include machine learning, deep learning networks, generative adversarial networks, deep reinforcement learning, self-supervised learning, extraction of robust features, object detection, semantic segmentation, linguistic descriptions of images, visual search, visual tracking, 3D shape retrieval, image inpainting, novelty and anomaly detection."--
Computer vision. --- Pattern recognition systems --- Data processing. --- Pattern recognition systems. --- Machine learning. --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern classification systems --- Pattern recognition computers --- Pattern perception --- Computer vision --- Data processing
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