Terrain Object Recognition
Terrain Object Recognition is a computational method that identifies and classifies distinct physical entities within a segmented terrain by analyzing spatial patterns, spectral signatures, and contextual features to differentiate objects of interest from their surrounding environment.
20
Publications
616
Citations
68
Authors
24
Institutions
Publications per year
2017–2026
7
Parents
20
AI4MARS: A Dataset for Terrain-Aware Autonomous Driving on Mars
R. Michael Swan, Deegan Atha, Henry A. Leopold et al. · 2021 · 93 citations
A hybrid attention semantic segmentation network for unstructured terrain on Mars
Haiqiang Liu, Meibao Yao, Xueming Xiao et al. · Acta Astronautica · 2022 · 58 citations
1–5 of 20
68
2
h-index
2
h-index
2
h-index
2
h-index
Decision Systems (United States), United States
2 publications · 40 citations
2
h-index
1–5 of 68
24

Harbin Institute of Technology
Harbin, China
2 h-index
6 publications
183 citations
Decision Systems (United States)
Northbrook, United States
2 h-index
5 publications
112 citations
National Research Council
Rome, Italy
2 h-index
4 publications
228 citations
Jet Propulsion Laboratory
Pasadena, United States
2 h-index
9 publications
677 citations
Nanyang Technological University
Singapore, Singapore
2 h-index
6 publications
76 citations

Changchun University of Science and Technology
Changchun, China
1 h-index
1 publications
58 citations
Florida A&M University - Florida State University College of Engineering
Tallahassee, United States
1 h-index
4 publications
68 citations
Jilin University
Changchun, China
1 h-index
2 publications
116 citations
1–8 of 24
2 publications · 53 citations
2
h-index
2 publications · 81 citations
2
h-index
1 publications · 60 citations
1
h-index
1 publications · 12 citations
1
h-index
1 publications · 23 citations
1
h-index
1–5