Infrared Ship Target Detection Method Based on Deep Convolution Neural Network

2018 ◽  
Vol 38 (7) ◽  
pp. 0712006
Author(s):  
王文秀 Wang Wenxiu ◽  
傅雨田 Fu Yutian ◽  
董峰 Dong Feng ◽  
李锋 Li Feng
IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 25972-25979 ◽  
Author(s):  
Guowei Xu ◽  
Xuemiao Su ◽  
Wei Liu ◽  
Chunbo Xiu

Author(s):  
Yan Wang ◽  
Weijie Zhang

Aiming at the problem of low detection accuracy of traditional power insulator fault detection methods, a power insulator fault detection method based on deep convolution neural network is designed. For the training of deep convolution neural network, the fault detection of power insulator based on deep convolution neural network is realized by anchor design, loss function design, candidate region selection mechanism establishment and sharing convolution features. The experimental results show that the fault detection method of power insulator based on deep convolution neural network is more accurate than the traditional method, and the detection time is less.


2019 ◽  
Vol E102.D (11) ◽  
pp. 2272-2275
Author(s):  
Menghan JIA ◽  
Feiteng LI ◽  
Zhijian CHEN ◽  
Xiaoyan XIANG ◽  
Xiaolang YAN

2021 ◽  
Vol 1971 (1) ◽  
pp. 012081
Author(s):  
SHEN Mengmeng ◽  
WANG Yong ◽  
MA Jiaqi ◽  
LI Chuanguo ◽  
HE Liangbo ◽  
...  

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