Paper
6 May 2022 Object recognition based on YOLO v3 network architecture in river patrol scene
Tao Feng, Mingxiang Yang
Author Affiliations +
Proceedings Volume 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022); 1225632 (2022) https://doi.org/10.1117/12.2635402
Event: 2022 International Conference on Electronic Information Engineering, Big Data and Computer Technology, 2022, Sanya, China
Abstract
With the development of science and technology, the application of artificial neural network and computer vision has become more extensive. Traditional river patrol methods have some inefficiencies and disadvantages in the quality of river patrol. To solve this problem, in this paper, we proposed an approach combined the high-performance YOLO v3 model with the SURF algorithm to detect illegal constructions and behaviors around the river bank. We first take image as the input of YOLO v3 model, then feed the output of YOLO v3 into the SURF algorithm to make a further detection. With this method, we can improve the quality of the river patrol, and enhance the ability to deal with illegal incidents around the river.
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Tao Feng and Mingxiang Yang "Object recognition based on YOLO v3 network architecture in river patrol scene", Proc. SPIE 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022), 1225632 (6 May 2022); https://doi.org/10.1117/12.2635402
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KEYWORDS
Video surveillance

Object recognition

Detection and tracking algorithms

Network architectures

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