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BFR-RetinaNet: An Improved RetinaNet Model for Vehicle Detection in Aerial Images

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成果类型:
会议论文
作者:
Zhang, J. I. N.;Luo, Meng;Sun, Cheng;Qu, Peiqi
作者机构:
[Qu, Peiqi; Zhang, J. I. N.] Hunan Normal Univ, Coll Informat Sci & Engn, Changsha, Peoples R China.
[Luo, Meng; Sun, Cheng] Hunan Normal Univ, Coll Math & Stat, Changsha, Peoples R China.
[Zhang, J. I. N.] Changsha Univ Sci & Technol, Sch Comp & Commun Engn, Changsha, Peoples R China.
语种:
英文
关键词:
Vehicle detection;Aerial imagery;Oriented bounding box;RetinaNet;Feature pyramid network
期刊:
Lecture Notes in Computer Science
ISSN:
0302-9743
年:
2022
卷:
13155
页码:
18-32
会议名称:
21st International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP)
会议论文集名称:
Lecture Notes in Computer Science
会议时间:
DEC 03-05, 2021
会议地点:
ELECTR NETWORK
会议主办单位:
[Zhang, J. I. N.;Qu, Peiqi] Hunan Normal Univ, Coll Informat Sci & Engn, Changsha, Peoples R China.^[Luo, Meng;Sun, Cheng] Hunan Normal Univ, Coll Math & Stat, Changsha, Peoples R China.^[Zhang, J. I. N.] Changsha Univ Sci & Technol, Sch Comp & Commun Engn, Changsha, Peoples R China.
主编:
Lai, Y Wang, T Jiang, M Xu, G Liang, W Castiglione, A
出版地:
GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
出版者:
SPRINGER INTERNATIONAL PUBLISHING AG
ISBN:
978-3-030-95384-3; 978-3-030-95383-6
基金类别:
Open Research Project of the StateKey Laboratory of Industrial Control Technology [ICT2021B10]; Natural Science Foundation of Hunan Province [2021JJ30456]; Open Fund of Science and Technology on Parallel and Distributed Processing Laboratory [WDZC20205500119]; Hunan Provincial Science and Technology Department High-tech Industry Science and Technology Innovation Leading Project [2020GK2009]; Scientific and Technological Progress and Innovation Program of the Transportation Department of Hunan Province [201927]
机构署名:
本校为其他机构
院系归属:
计算机与通信工程学院
摘要:
Vehicle detection in aerial images has been applied in many fields and attracted more and more scholars' attention. In the task, the objects are multidirectional and arranged densely, the background information is complex, and the scale of the object is different. To achieve better detection performance, an improved detection model BFR-RetinaNet is proposed, which is based on the single-stage object detection model RetinaNet. BFR-RetinaNet optimizes vehicle positioning by adding a directional anchor box regression branch. Simultaneously, the model introduces a balanced feature pyramid structur...

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