Remote Sensing | 卷:12 |
ℱ3-Net: Feature Fusion and Filtration Network for Object Detection in Optical Remote Sensing Images | |
Yuntao Qian1  Xinhai Ye2  Jianfeng Lu2  Fengchao Xiong2  Jun Zhou3  | |
[1] Institute of Artificial Intelligence, College of Computer Science, Zhejiang University, Hangzhou 310027, China; | |
[2] School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China; | |
[3] School of Information and Communication Technology, Griffith University, Nathan 4111, Australia; | |
关键词: context information; object detection; feature filtration; convolutional neural networks (CNNs); optical remote sensing image; | |
DOI : 10.3390/rs12244027 | |
来源: DOAJ |
【 摘 要 】
Object detection in remote sensing (RS) images is a challenging task due to the difficulties of small size, varied appearance, and complex background. Although a lot of methods have been developed to address this problem, many of them cannot fully exploit multilevel context information or handle cluttered background in RS images either. To this end, in this paper, we propose a feature fusion and filtration network (
【 授权许可】
Unknown