YOLO Series Target Detection Technology and Application

Author:

Zhang Yuan

Abstract

Recently, YOLO is the most popular algorithm in machine learning. The algorithm has developed rapidly, and there are several versions at present. Each version of the framework is different, and they also have their own application areas. And maybe in one area, not only one version can be used. This paper summarizes the process of target detection, the structures of YOLO network. In addition, this work also analyzed the development, advantages and disadvantages of YOLO target detection. Finally, the application of YOLO in automatic driving and UAV detection are discussed. YOLO may develop faster in the future. YOLO model is a variable model, which has unique functions when detecting different things under different circumstances. At the end of the paper, the thesis is summarized, and the related research has certain reference value.

Publisher

Darcy & Roy Press Co. Ltd.

Reference10 articles.

1. Bevilacqua V, Triggiani M, Gallo V, et al. Intelligent Computing Theories and Applications. Springer Berlin Heidelberg, 2010.

2. Zhihong Zhang, Huajun Gong, Xinhua Wang, Yadong Feng, Minjie Xu. An Improved Yolov3 Object Detection Algorithm for UAV Aerial Images, 2021 International Conference on Intelligent Computing, Automation and Applications (ICAA), 2021, 191(13): 153-158.

3. Malik Haris, Jin Hou, Xiaomin Wang. Lane Lines Detection under Complex Environment by Fusion of Detection and Prediction Models, Transportation Research Record: Journal of the Transportation Research Board, 2014, 110(10): 503-511.

4. Ghada Hamed Aly, Mohammed Abd El- Rahman Marey, Safaa El-Sayed Amin, Mohamed Fahmy Tolba. Chapter 15 YOLO V3 and YOLO V4 for Masses Detection in Mammograms with ResNet and Inception for Masses Classification, Springer Science and Business Media LLC, 2021: 1342-1351.

5. Huang D S , Mcginnity M , Heutte L , et al. Advanced Intelligent Computing Theories and Applications. Communications in Computer and Information Science, 2010, 93.

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1. Driverless Image Processing Based on Improved YOLOv5l;2023 7th Asian Conference on Artificial Intelligence Technology (ACAIT);2023-11-10

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