引入通道注意力和残差学习的目标检测器

doi:10.16451/j.cnki.issn1003-6059.202010003

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Abstract The feature information of feature maps of different scales cannot be fully utilized by the existing feature pyramid of target detectors, and these detectors are not suitable for the detection of low-resolution image targets and small targets. To solve this problem, a target detector with channel attention mechanism and residual learning block is proposed. Firstly, the channel global attention mechanism is introduced to learn the weights of different channel features in the feature map through the network and thus the global feature information is enhanced effectively. Then, lightweight residual blocks are exploited to highlight small changes of features and improve the detection performance for small targets in low-resolution images. In addition, deep features are merged into the shallow feature maps for prediction to improve the detection accuracy of small targets. The experimental results on standard test datasets show that the proposed target detector is suitable for low-resolution images and obtains a better detection result for small targets.

Key words： Target Detection Feature Pyramid Global Feature Enhancement Residual Learning

Received: 21 May 2020

ZTFLH:	TP183
	TP391

Fund:National Natural Science Foundation of China(No.61663031,61866028,61661036), Foundation of China Scholarship Council(No.CSC201908360075), the Key Program Project of Research and Development of Science and Technology Department of Jiangxi Province(No.20171ACE50024,20192BBE50073)

Corresponding Authors: CHU Jun, Ph.D., professor. Her research interests include com-puter vision and pattern recognition.

About author:: ZHU Xiaoyang, master student. Her research interests include computer vision and target detection.LENG Lu, Ph.D., associate professor. His research interests include image processing and biometric template.MIAO Jun, Ph.D., associate professor. His research interests include computer vision, 3D reconstruction and pattern recognition.

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	CHU Jun
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Cite this article:

CHU Jun,ZHU Xiaoyang,LENG Lu等. Target Detector with Channel Attention and Residual Learning[J]. , 2020, 33(10): 889-897.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202010003 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2020/V33/I10/889

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