Computer Vision
Object Detection
Identifying and localizing objects within an image by drawing bounding boxes around them.
In-depth explanation
Object detection combines classification (what) with localization (where). Two-stage detectors (R-CNN family) first propose regions then classify; one-stage detectors (YOLO, SSD) predict boxes and classes simultaneously for faster inference. Metrics include mAP (mean Average Precision). Applications include autonomous driving, security, and retail.
Examples
YOLO detecting cars and pedestrians
Retail product detection
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