Implement YOLO(You Only Look Once)to Detect Objects in Image
Authors:-Dr. M.V. Subba Reddy, Yendluri.Suchitra, Shaike. Humera Bhanu, Thati. Ganga Maheswari, Pasam.Venkatesh
Abstract-Object recognition plays a crucial role in various real-world applications, including surveillance, autonomous vehicles, and robotics. This paper presents an efficient object detection and recognition system using the You Only Look Once (YOLO) deep learning model. YOLO is a state-of-the-art, real-time object detection framework that processes an entire image in a single forward pass, making it significantly faster than traditional region-based approaches. The proposed system is implemented using YOLOv5, leveraging a Convolutional Neural Network (CNN) for feature extraction and classification. The model is trained on large-scale datasets, such as COCO, to recognize multiple objects with high accuracy. We evaluate the system’s performance based on mean Average Precision (mAP), inference speed, and real-time detection capabilities. Experimental results demonstrate that YOLO achieves robust object recognition with minimal latency, making it suitable for real-time applications.
