Automatic Rocks Segmentation Based on Deep Learning for Planetary Rover Images
Author:
Affiliation:
1. China Academy of Space Technology, 100094 Beijing, People’s Republic of China
2. Beihang University, 100191 Beijing, People’s Republic of China
Funder
National Natural Science Foundation of China
Publisher
American Institute of Aeronautics and Astronautics (AIAA)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Aerospace Engineering
Link
https://arc.aiaa.org/doi/pdf/10.2514/1.I010925
Reference21 articles.
1. High-precision navigation and positioning of celestial exploration rover based on depth camera
2. Texture analysis for Mars rover images
3. Autonomous rock detection for Mars terrain
4. Automated rock detection and shape analysis from mars rover imagery and 3D point cloud data
5. Rockster: Onboard Rock Segmentation Through Edge Regrouping
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1. Automated Rock Detection From Mars Rover Image via Y-Shaped Dual-Task Network With Depth-Aware Spatial Attention Mechanism;IEEE Transactions on Geoscience and Remote Sensing;2024
2. RockSeg: A Novel Semantic Segmentation Network Based on a Hybrid Framework Combining a Convolutional Neural Network and Transformer for Deep Space Rock Images;Remote Sensing;2023-08-09
3. Towards a Biosignatures Image Detection System for Planetary Exploration with UAVs;2023 IEEE Aerospace Conference;2023-03-04
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