Aircraft target detection and fine-grained recognition based on RHTC network

被引：0
|
作者：
Cao X. [1 ]
Zou H. [1 ]
Cheng F. [1 ]
Li R. [1 ]
He S. [1 ]
机构：
[1] College of Electronic Science and Technology, National University of Defense Technology, Changsha
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2021年 / 43卷 / 12期
关键词：
Aircraft target; Direction detection; Fine-grained recognition (RHTC); High resolution remote sensing image; Rotated hybrid task cascade network;
D O I：
10.12305/j.issn.1001-506X.2021.12.04
中图分类号：
学科分类号：
摘要：
Direction detection and fine-gained recognition of aircraft targets is an important task in the field of high-resolution optical remote sensing image interpretation. Aiming at the difficulty of direction detection and recognition of multi-directional densely arranged aircraft in remote sensing images, an aircraft detection and recognition method based on rotating hybrid task cascade (RHTC) network is proposed. Firstly, based on hybrid task cascade (HTC) network, the number of segmented branches is expanded, and the segmented branches and bounding box branches are cascaded at multiple levels to continuously strengthen semantic features. Secondly, a new slant frame regressor is designed and added to the last layer of the mask branch to complete the target direction prediction. Finally, a new directional loss function is added to optimize the training process, so as to complete the construction of RHTC network. In the data preprocessing stage, the fine mask of each type of aircraft target is constructed to enhance the target detail and improve the mask prediction accuracy. Several groups of experiments were carried out on aircraft data sets constructed based on DOTA and public Google images. The results show that compared with other advanced methods, the proposed method has better performance in aircraft detection direction accuracy and category average accuracy. In addition, the designed skew frame regressor and directional loss function also have good performance when embedded into other segmented networks. © 2021, Editorial Office of Systems Engineering and Electronics. All right reserved.
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页码：3439 / 3451
页数：12
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