Report on the 2022 IEEE Geoscience and Remote Sensing Society Data Fusion Contest: Semisupervised Learning [Technical Committees]-Reference-Cited by-同舟云学术

Report on the 2022 IEEE Geoscience and Remote Sensing Society Data Fusion Contest: Semisupervised Learning [Technical Committees]

Published:2022-12 Issue:4 Volume:10 Page:270-273
ISSN:2168-6831
Container-title:IEEE Geoscience and Remote Sensing Magazine
language:
Short-container-title:IEEE Geosci. Remote Sens. Mag.

Author:

Hansch Ronny¹^ORCID,Persello Claudio²^ORCID,Vivone Gemine³^ORCID,Navarro Javiera Castillo⁴^ORCID,Boulch Alexandre⁵,Lefevre Sebastien⁶^ORCID,Saux Bertrand Le⁷^ORCID

Affiliation:

1. Radar Technology, DLR Oberpfaffenhofen, Oberpfaffenhofen-Wessling, Bavaria, Germany

2. Earth Observation Science, University of Twente, Enschede, Overijssel, Netherlands

3. CNR-IMAA atmospheric observatory, Inst. of Methodologies for Environ. Analysis, Basilicata, Tito Scalo, Italy

4. DTIS, ONERA Traitement de l’information et systemes, Palaiseau, Ile de France, France

5. Valeo.ai, Paris, France

6. IRISA, Universite de Bretagne Sud, Vannes, France

7. Phi lab, ESRIN, Frascati, RM, Italy

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,General Earth and Planetary Sciences,Instrumentation,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6245518/10049233/09956742.pdf?arnumber=9956742

Reference24 articles.

1. Advanced Multi-Sensor Optical Remote Sensing for Urban Land Use and Land Cover Classification: Outcome of the 2018 IEEE GRSS Data Fusion Contest

2. Semi-Supervised Land-Cover Mapping Based on Multimodal Fusion and Pseudo-Label

3. Open Data for Global Multimodal Land Use Classification: Outcome of the 2017 IEEE GRSS Data Fusion Contest

4. Class-Aware Regularized Self-Distillation Learning Method for Land Cover Classification

5. Large-Scale Semantic 3-D Reconstruction: Outcome of the 2019 IEEE GRSS Data Fusion Contest—Part B

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