objectrecognition
Object recognition is a subfield of computer vision and pattern recognition that focuses on identifying and classifying objects within images or video frames. It encompasses tasks such as determining what objects appear in a scene (classification) as well as locating them (detection) and, in more advanced forms, identifying specific instances or delineating their boundaries (segmentation).
Historically, object recognition relied on hand-crafted features such as SIFT, HOG, and bag-of-words representations. The emergence
Common datasets include ImageNet for classification, and COCO, PASCAL VOC, and Open Images for detection and
Applications span autonomous vehicles, robotics, surveillance, image search, and augmented reality. Key challenges include occlusion, scale
Typical workflow involves data collection and annotation, preprocessing, model training, evaluation, and deployment. Ethical considerations include