A detection model is a machine learning model designed to locate and identify specific objects, events, or patterns within input data. Unlike a simple classification model that assigns one label to an entire input, a detection model can determine what is present and where it occurs. Depending on the application, it may return locations such as bounding boxes, regions, or coordinates along with confidence scores.
Detection models are widely used in computer vision for tasks such as identifying vehicles in traffic footage, locating defects on manufactured parts, or detecting people in security images. Modern models can process images or video rapidly enough for applications such as automated inspection and real-time monitoring. Related concepts include object detection, image classification, computer vision, deep learning, and segmentation.
