Automated Feature Recognition
Automated Feature Recognition is a methodological framework within remote sensing and three-dimensional modeling automation that enables the systematic identification and extraction of geospatial features from sensor data through algorithmic processing, distinguishing itself from manual or semi-automated approaches by its reliance on computational intelligence to minimize human intervention.
203
Publications
10.4K
Citations
691
Authors
290
Institutions
Publications per year
2017–2026
63
203
Cooperative methods for road tracking in aerial imagery
David M. McKeown, Jerry L. Denlinger · 2003 · 223 citations
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Arizona State University
Tempe, United States
8 h-index
16 publications
410 citations

Drexel University
Philadelphia, United States
4 h-index
4 publications
354 citations
University of Southern California
Los Angeles, United States
3 h-index
7 publications
232 citations
University of Wisconsin–Madison
Madison, United States
3 h-index
5 publications
200 citations
Georgia Institute of Technology
Atlanta, United States
3 h-index
5 publications
111 citations
Lockheed Martin (United States)
Bethesda, United States
3 h-index
3 publications
251 citations

Zhejiang University
Hangzhou, China
3 h-index
7 publications
274 citations
Purdue University West Lafayette
West Lafayette, United States
3 h-index
5 publications
840 citations
1–8 of 290
10 publications · 547 citations
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8 publications · 214 citations
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6 publications · 228 citations
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4 publications · 105 citations
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3 publications · 119 citations
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