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Machine Vision as a book category covers the theory, methods, tools and applications for enabling machines to interpret visual data—spanning image processing, feature extraction, pattern recognition, classical and deep learning approaches to object detection, segmentation, 3D reconstruction, motion analysis and scene understanding. It is interdisciplinary, combining computer science, electrical engineering, optics and AI, and includes textbooks, research monographs, practitioner guides and applied case studies that address sensors and cameras (including LiDAR), datasets and benchmarks, hardware and deployment, performance evaluation and optimization. Books in this category target students, researchers and engineers building systems for industrial inspection, robotics, autonomous vehicles, medical imaging, remote sensing and surveillance, and often discuss practical implementation, scalability, and ethical and safety considerations.

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