Light weight rotating object detector based on angle sensitive spatial attention mechanism

With the rapid development of deep learning, more and more target detection algorithms based on anchor frame are applied to remote sensing images in recent years.However, the cost of improving the accuracy of the algorithm is to sacrifice the detection speed.Therefore, the target detection network f...

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Bibliographic Details
Main Authors: Kaishi YIN, Meng YANG, Xi GU, Zhicheng WANG
Format: Article
Language:zho
Published: POSTS&TELECOM PRESS Co., LTD 2021-09-01
Series:智能科学与技术学报
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Online Access:http://www.cjist.com.cn/thesisDetails#10.11959/j.issn.2096-6652.202133
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Summary:With the rapid development of deep learning, more and more target detection algorithms based on anchor frame are applied to remote sensing images in recent years.However, the cost of improving the accuracy of the algorithm is to sacrifice the detection speed.Therefore, the target detection network framework of anchor free was chosen, and a remote sensing detection algorithm of rotating frame was proposed according to the characteristics of remote sensing scene.A simple and effective representation of rotating frame was proposed according to the spatial position relationship between rotating frame and its external rectangular frame.In addition, an angle sensitive attention mechanism was designed to assist the detection of rotating targets.By introducing angle information, the detection ability of the model for rotating targets was improved.The proposed algorithm was tested on the open remote sensing dataset DOTA.The mean average precision of target detection network of rotating frame is 68.5% and the detection speed is 17.4 frames per second.
ISSN:2096-6652