[1]ZHAO Wenqing,CHENG Xingfu,ZHAO Zhenbing,et al.Insulator recognition based on attention mechanism and Faster RCNN[J].CAAI Transactions on Intelligent Systems,2020,15(1):92-98.[doi:10.11992/tis.201907023]
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Insulator recognition based on attention mechanism and Faster RCNN

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 15 Number of periods: 2020 1 Page number: 92-98 Column: 学术论文—机器感知与模式识别 Public date: 2020-01-05
Title:
Insulator recognition based on attention mechanism and Faster RCNN
Author(s):
ZHAO Wenqing1;  CHENG Xingfu1;  ZHAO Zhenbing2;  ZHAI Yongjie1
1. School of Control and Computer Engineering, North China Electric Power University, Baoding 071003, China;
2. School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China
Keywords:
Faster RCNN; insulator; attention mechanism; SENet; characteristic channel; RPN; proposal boxes; feature vector
CLC:
TP391
DOI:
10.11992/tis.201907023
Abstract:
In order to solve the problem of inaccurate location in the process of recognizing insulator image using Faster RCNN, this paper proposes an insulator recognition method based on attention mechanism and Faster RCNN. Firstly, the Squeeze-and-Excitation Networks (SENet) structure based on attention mechanism is introduced in the feature extraction stage to enable the model to focus on the target-related feature channels and weaken other irrelevant feature channels. Then, according to the characteristics of insulators, the proportion and scale of anchors generated by regional proposal network (RPN) are adjusted. Finally, the attention mechanism is applied in the full connected layer to give different weights to the feature vectors of the surrounding suggestion boxes and fuse them to update the feature vectors of the target suggestion boxes. The experimental results show that the improved algorithm can recognize insulators better than the traditional Faster RCNN algorithm.
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