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Definition:
Object Detection /ˈɒb.dʒɪkt dɪˈtɛk.ʃən/ noun — In computer vision and artificial intelligence, object detection refers to the task of identifying and localizing multiple objects within an image or video frame. It goes beyond simple image classification by not only determining what objects are present, but also where they are located using bounding boxes.
Object detection is essential in real-world applications such as:
- Autonomous driving (detecting pedestrians, vehicles, signs)
- Security and surveillance systems
- Retail analytics and inventory tracking
- Augmented reality and robotics
This task is typically performed using deep learning models such as:
- YOLO (You Only Look Once)
- Faster R-CNN (Region-based Convolutional Neural Network)
- SSD (Single Shot Detector)
Modern object detection systems are trained on large datasets (e.g., COCO, PASCAL VOC) and achieve real-time performance by combining feature extraction, classification, and localization in a single end-to-end pipeline.
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