A robust end-to-end deep learning framework for detecting Martian landforms with arbitrary orientations

被引：0
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作者：
Jiang, Shancheng [1 ]
Wu, Fan [2 ]
Yung, K.L. [1 ]
Yang, Yingqiao [1 ]
Ip, W.H. [1 ]
Gao, Ming [3 ,4 ]
Foster, James Abbott [1 ]
机构：
[1] Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom,Kowloon,999077, Hong Kong
[2] School of Intelligent Systems Engineering, Sun Yat-Sen University, No. 135, Xingang Xi Road, Guangzhou,510275, China
[3] School of Management Science and Engineering, Dongbei University of Finance and Economics, No. 217 Jianshan Street, Shahekou District, Dalian,116025, China
[4] Center for Post-doctoral Studies of Computer Science, Northeastern University, Shenyang, China
来源：
Knowledge-Based Systems | 2021年 / 234卷
关键词：
This work was supported in part by the project grant ZG3K Chang’e phase 3 sample return instruments; in part by the National Nature Science and Foundation of China Grand No. 71801031; in part by the Guangdong Basic and Applied Basic Research Foundation project; China; No; 2019A1515011962; and; 2020A1515110431; in part by the National Nature Science and Foundation of China Grand No. 71772033; in part by the Natural Science Foundation of Liaoning Province; China (Joint Funds for Key Scientific Innovation Bases; 2020-KF-11-11; and in part by the Scientific Research Project of the Education Department of Liaoning Province; LN2019Q14;
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