Research on a Vision-Based Suspicious Target Recognition Algorithm in Reservoir Area

被引：0

作者：

Li X. ^{[1
]}

Chen Y. ^{[1
,2
]}

Wang Z. ^{[3
]}

Luo X. ^{[1
]}

Li C. ^{[2
]}

Hou X. ^{[4
,5
]}

机构：

[1] Department of Weapons and Control, Army Armored Forces College, Beijing

[2] 63850 Troops of the Chinese People's Liberation Army, Jilin

[3] 32108 Troops of the Chinese People's Liberation Army, Manzhouli

[4] Journal of Chongqing University, Chongqing University, Chongqing

[5] College of Automation, Chongqing University, Chongqing

来源：

Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology | 2022年 / 42卷 / 04期

关键词：

Classifier; Feature extraction; Neural network; Target recognition;

D O I：

10.15918/j.tbit1001-0645.2021.106

中图分类号：

学科分类号：

摘要：

Aiming at the requirement of intelligent recognition of image targets by the storage area inspection image acquisition equipment, a vision-based long-distance suspicious target recognition algorithm was designed and implemented. Firstly, a target detection method was used to identify and collect the target image. And then, the convolution layer of the deep learning model based on convolutional neural network was used to extract the features of the target image, and the shallow network based on the traditional machine learning method was used to classify the suspicious target. Finally, an experiment was designed according to the algorithm. The experimental results show that the algorithm model can improve recognition effect, can effectively reduce the workload of manual recognition, and can meet the requirements of actual application. Copyright ©2022 Transaction of Beijing Institute of Technology. All rights reserved.

引用

页码：424 / 429

页数：5

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