| Title | Level-Wise Band-Partition-Based Hierarchical Representation Residual Feature Learning for Hyperspectral Target Detection |
| Author | |
| DOI | |
| Publication Years | 2023
|
| ISSN | 2161-8070
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| ISBN | 979-8-3503-2070-1
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| Source Title | |
| Pages | 1-5
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| Conference Date | 26-30 Aug. 2023
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| Conference Place | Auckland, New Zealand
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| Keywords | |
| SUSTech Authorship | Others
|
| URL | [Source Record] |
| Data Source | IEEE
|
| PDF url | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10260558 |
| Citation statistics | |
| Document Type | Conference paper |
| Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/582702 |
| Affiliation | 1.School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China 2.Sifakis Research Institute for Trustworthy Autonomous Systems, Southern University of Science and Technology, Shenzhen, China 3.Guangdong Laboratory of Artificial Intelligence and Digital Economy (Shenzhen), Shenzhen, China |
| Recommended Citation GB/T 7714 |
Tan Guo,Jiakun Guo,Dachun Li,et al. Level-Wise Band-Partition-Based Hierarchical Representation Residual Feature Learning for Hyperspectral Target Detection[C],2023:1-5.
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| Files in This Item: | There are no files associated with this item. | |||||
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