Object detection identifies and locates multiple objects within an image by drawing bounding boxes around them and assigning class labels with confidence scores. Unlike simple image classification that labels an entire image, detection pinpoints where each object is. Popular architectures include YOLO, Faster R-CNN, and DETR. Applications include autonomous driving, surveillance, quality inspection in manufacturing, and inventory management in retail.