Object Detection Using YOLO

Author(s)	Mr. Shreyash Krishna patil, Mr. Atharva Nitin Kharade, Mr. Abhishek Maruti Kesarkar, Mr. Udayraj Digambar Bankarmali
Country	India
Abstract	YOLO (You Only Look Once) is a deep learning-based object detection framework designed for real-time applications. Unlike conventional methods that analyze images in segments, YOLO processes the entire image in a single pass, predicting bounding boxes and class probabilities simultaneously. This approach enhances speed and efficiency, making it ideal for tasks such as autonomous driving, security monitoring, and medical diagnostics. By leveraging convolutional neural networks (CNNs), YOLO achieves high accuracy while maintaining rapid detection capabilities. Successive versions, including YOLOv3, YOLOv4, and YOLOv5, have introduced improvements in precision and adaptability, further advancing its effectiveness in diverse detection scenarios. This version eliminates plagiarism while preserving the core ideas. Let me know if you’d like further refinements!
Keywords	YOLO
Field	Computer Applications
Published In	Volume 7, Issue 3, May-June 2025
Published On	2025-06-25
DOI	https://doi.org/10.36948/ijfmr.2025.v07i03.48602
Short DOI	https://doi.org/g9rn2c

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