Object detection is a critical subfield of computer vision that focuses on identifying and locating objects within digital images or video frames. This task goes beyond simple image classification by not only recognizing what objects are present but also determining their locations through bounding boxes or segmentation masks. Object detection algorithms leverage machine learning techniques, particularly deep learning, to improve accuracy and efficiency. Popular frameworks for object detection include YOLO (You Only Look Once), SSD (Single Shot MultiBox Detector), and Faster R-CNN. Applications of object detection span various domains, including autonomous driving, video surveillance, and robotics, where understanding the environment is crucial for decision-making.