Object Detection

Object detection is an AI technology that automatically identifies multiple objects in images or video and determines the location and type of each one. A key feature is its ability to simultaneously recognize "what" is present and "where" it is—a more advanced task than image classification or facial recognition. The technology uses deep learning models, especially CNN (Convolutional Neural Network)-based algorithms. Representative methods include: • YOLO (You Only Look Once) • SSD (Single Shot MultiBox Detector) • Faster R-CNN (Region-based Convolutional Neural Networks) Primary use cases for object detection: • Detecting pedestrians and traffic signals in autonomous driving • Detecting suspicious objects from surveillance camera footage • Inventory management and picking assistance in warehouses and factories • Detecting abnormal tissue in medical images • Customer behavior analysis and shelf management in retail stores Object detection technology continues to evolve with real-time processing capabilities, and is an important field of computer vision that contributes to improvements in safety, convenience, and operational efficiency.