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Object Recognition is a category focused on the theories, algorithms, and practical methods for detecting, classifying, and identifying objects in images, video, and 3D data. Books span introductory computer vision and pattern recognition texts to advanced works on deep learning (e.g., CNNs and vision transformers), feature engineering, 3D perception, and multimodal approaches. Common topics include dataset curation and annotation, training and evaluation metrics, robustness and bias, real-time performance, and deployment on edge and cloud platforms. The category highlights applications in robotics, autonomous driving, medical imaging, industrial inspection, retail, security, and augmented reality, and may also include titles on human visual perception from psychology and neuroscience. It serves students, researchers, and practitioners building systems that perceive and interpret the visual world.

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