Martin Jagersand: h-index, Total Citations, and Citation Map
Martin Jagersand's h-index is 1 (1 i10-index, 10,657+ total citations across 1+ publications) according to Google Scholar as of June 2026. Martin Jagersand is affiliated with Professor, University of Alberta, Alberta Canada.
Martin Jagersand is a researcher affiliated with Professor, University of Alberta, Alberta Canada, specializing in AI & Machine Learning. Their work has been cited 10,657 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Martin Jagersand's Citation Metrics
Bibliometric impact based on 1 indexed publication.
- H-Index
- 1
- i10-Index
- 1
- Total Citations
- 10,657
- Citing Countries
- 4
As of June 2026.
Martin Jagersand has an h-index of 1 and 10,657 total citations across 1 publication, with research cited by institutions in 4 countries.
Global Impact Map
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U$^2$-Net: Going deeper with nested U-structure for salient object detection
20202,775
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Martin Jagersand's research
Martin Jagersand is a researcher in AI & Machine Learning at Professor, University of Alberta, Alberta Canada. Their work has been cited 10,657 times across 1 publications, according to Google Scholar.
Their most-cited work, “U$^2$-Net: Going deeper with nested U-structure for salient object detection” (2020), has accumulated 2,775 citations.
Citations of Martin Jagersand's research come primarily from China, Hong Kong and Singapore, reflecting international research impact across 4+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
