Mars Terrain Segmentation with Less Labels-Reference-Cited by-同舟云学术

Mars Terrain Segmentation with Less Labels

Published:2022-03-05 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Aerospace Conference (AERO)
language:
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Author:

Goh Edwin¹,Chen Jingdao²,Wilson Brian¹

Affiliation:

1. Jet Propulsion Laboratory, California Institute of Technology

2. Mississippi State University,Computer Science and Engineering

Funder

Jet Propulsion Laboratory

California Institute of Technology

National Aeronautics and Space Administration

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9843190/9843194/09843245.pdf?arnumber=9843245

Reference37 articles.

1. Associative em-bedding: End-to-end learning for joint detection and grouping;newell;Proceedings of the 31st International Conference on Neural Information Processing Systems ser NIPS’17,2017

2. MSeg: A Composite Dataset for Multi-Domain Semantic Segmentation

3. Cross-Domain Semantic Segmentation via Domain-Invariant Interactive Relation Transfer

4. Semi-Supervised Semantic Segmentation With Cross-Consistency Training

5. Rethinking atrous convolution for semantic image segmentation;chen;CoRR,2017

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