State-of-the-Art Applications in Computer Vision for Real-Time Target Detection: A Comprehensive Overview

This study presents a computer vision module for real-time target detection in live video feeds utilising a deep learning object detector based on the YOLO technique. By pre-training on a sizable target picture dataset, adding a lightweight attention mechanism, and using post-processing to eliminate false positives and improve bounding boxes, it improves YOLO’s accuracy. Modern precision is attained by the module on difficult real-world video[4]. It also examines new developments in real-time object identification, such as transfer learning, noise and occlusion resistance, and innovative structures. This programme has potential applications in robotics, surveillance, and augmented reality.