Multi-Label Noise Robust Collaborative Learning for Remote Sensing Image Classification
Author:
Affiliation:
1. Faculty of Electrical Engineering and Computer Science, Technische Universität Berlin, Berlin, Germany
Funder
European Research Council (ERC) through the
BigEarth Project
German Ministry for Education and Research through the Berlin Institute for the Foundations of Learning and Data
TreeSatAI Project
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software
Link
http://xplorestaging.ieee.org/ielx7/5962385/6104215/09926002.pdf?arnumber=9926002
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2. Analyzing and Improving the Quality and Fitness for Purpose of OpenStreetMap as Labels in Remote Sensing Applications;Volunteered Geographic Information;2023-12-09
3. Cnns in land cover mapping with remote sensing imagery: a review and meta-analysis;International Journal of Remote Sensing;2023-09-25
4. Label Noise Robust Image Representation Learning Based on Supervised Variational Autoencoders in Remote Sensing;IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium;2023-07-16
5. Semantic and Correlation Disentangled Graph Convolutions for Multilabel Image Recognition;IEEE Transactions on Neural Networks and Learning Systems;2023
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