Joseph Redmon is a researcher affiliated with Ai2, specializing in AI & Machine Learning. Their work has been cited 158,018 times. This profile visualizes their global influence, highlighting strong citation networks in GB.
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Bibliometric impact based on 1 indexed publication.
As of April 2026.
Joseph Redmon has an h-index of 1 and 158,018 total citations across 1 publication, with research cited by institutions in 2 countries.
Visualizing the geographic distribution of institutions that have cited your work.
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.
Visa-ready visualisation: each outer ring node is a country citing this scholar. Node size & edge weight scale with citing-paper count. Showing top 2 of 2 countries (3 total citations).
Ranked by EB-1A / O-1A relevance: independence from your home institution, affiliation with a top-ranked institution, repeat citations of your work, and recency. Reach out to the highest-scoring candidates to request support letters.
I-Hau Yeh
8.5National Taipei University of Technology
Taiwan· Cited your work 1 time
Rahima Khanam
5.0Huddersfield University
UK· Cited your work 1 time
Muhammad Hussain
5.0Huddersfield University
UK· Cited your work 1 time
Scores combine 5 signals: independence (+3), prestige institution (+2), repeat citations (+2 per paper, cap 5), recent activity (+1), and geography diversity (+1.5). Identity matching uses name + institution; namesakes at the same org are merged.
Citations flagged as non-independent share the scholar's home institution (University of Washington). EB-1A & O-1A petitions typically quote the independent-citation count as the stronger evidence of outside recognition.
Rahima Khanam, Muhammad Hussain
arXiv (Computer Science > Computer Vision and Pattern Recognition); YOLO Vision 2024 (YV24)· cites “You Only Look Once: Unified, Real-Time Object Detection”
· cites “You Only Look Once: Unified, Real-Time Object Detection”
· cites “You Only Look Once: Unified, Real-Time Object Detection”
I-Hau Yeh, Chien-Yao Wang, Hong-Yuan Mark Liao
European Conference on Computer Vision (ECCV) 2024· cites “You Only Look Once: Unified, Real-Time Object Detection”
· cites “You Only Look Once: Unified, Real-Time Object Detection”
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