Charless Fowlkes Google Scholar: h-index, Total Citations, and Citation Map
Charless Fowlkes's h-index is 63 (124 i10-index, 38,763+ total citations across 210+ publications) according to Google Scholar as of October 2026. Charless Fowlkes is affiliated with Department of Computer Science, University of California, Irvine.
Charless Fowlkes is a researcher affiliated with Department of Computer Science, University of California, Irvine, specializing in various fields. Their work has been cited 38,763 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Charless Fowlkes's Citation Metrics
Bibliometric impact based on 210 indexed publications.
- H-Index
- 63
- i10-Index
- 124
- Total Citations
- 38,763
- Citing Countries
- 29
As of October 2026.
Charless Fowlkes has an h-index of 63 and 38,763 total citations across 210 publications, with research cited by institutions in 29 countries.
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A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
200111,175
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
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Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
21 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher established a foundational benchmark for image segmentation by creating a database of human-segmented natural images, enabling rigorous algorithm evaluation and ecological statistics measurement.
The researcher developed a seminal framework for contour detection and hierarchical image segmentation, establishing a foundational approach widely adopted across computer vision.
The researcher developed a foundational method for detecting natural image boundaries by integrating local brightness, color, and texture cues, establishing a seminal benchmark in computer vision.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Charless Fowlkes's research
Charless Fowlkes is a researcher at Department of Computer Science, University of California, Irvine. Their work has been cited 38,763 times across 210 publications (h-index 63), according to Google Scholar.
Their most-cited work, “A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics” (2001), has accumulated 11,175 citations. Other influential works include “Contour detection and hierarchical image segmentation” (2010) with 7,268 citations and “Learning to detect natural image boundaries using local brightness, color, and texture cues” (2004) with 3,362 citations.
Citations of Charless Fowlkes's research come primarily from China, United States and United Kingdom, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
