Low-cost Mars Terrain Classification System Based on Coarse-grained Annotation
Author:
Affiliation:
1. Research Center for Intelligent Robotics, Research Institute of Interdisciplinary Innovation,Zhejiang Laboratory,Hangzhou,China,311100
2. Dalhousie University,Department of Electrical and Computer Engineering,Halifax,NS,Canada,B3H 4R2
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10011626/10011636/10011884.pdf?arnumber=10011884
Reference25 articles.
1. Self-supervised terrain classification for planetary surface exploration rovers
2. A survey on recent object detection techniques useful for monocular vision-based planetary terrain classification
3. Stereo vision and rover navigation software for planetary exploration
4. A curvature-based approach to terrain recognition
5. Autonomous rock detection for Mars terrain
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1. Deep Learning based Terrain Classification of Mars Raw Images using UNet and FCN Models;2024 11th International Conference on Computing for Sustainable Global Development (INDIACom);2024-02-28
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