Remote Sensing Image Land Cover Classification with Label Noise Based on Deep Reinforcement Learning
Author:
Affiliation:
1. Wuhan University,State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing,Wuhan,China,430079
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10640349/10640352/10642816.pdf?arnumber=10642816
Reference11 articles.
1. Transformers in Remote Sensing: A Survey
2. Cross-resolution national-scale land-cover mapping based on noisy label learning: A case study of China
3. Google Earth Engine: Planetary-scale geospatial analysis for everyone
4. Global land cover mapping at 30m resolution: A POK-based operational approach
5. Good practices for estimating area and assessing accuracy of land change
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