Wangpeng An: h-index, Total Citations, and Citation Map
Wangpeng An's h-index is 11 (11 i10-index, 1,585+ total citations across 5+ publications) according to Google Scholar as of May 2026. Wangpeng An is affiliated with Tiktok inc..
Wangpeng An is a researcher affiliated with Tiktok inc., specializing in Computer Vision, Machine Learning. Their work has been cited 1,585 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Wangpeng An's Citation Metrics
Bibliometric impact based on 5 indexed publications.
- H-Index
- 11
- i10-Index
- 11
- Total Citations
- 1,585
- Citing Countries
- 11
As of May 2026.
Wangpeng An has an h-index of 11 and 1,585 total citations across 5 publications, with research cited by institutions in 11 countries.
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Global Impact Map
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Top Cited Works
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Detecting non-hardhat-use by a deep learning method from far-field surveillance videos
2018689
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.
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.
23 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher developed a deep learning method for detecting non-hardhat-use from far-field surveillance videos, establishing a foundational approach for automated safety compliance monitoring.
The researcher developed a deep learning method for detecting non-certified work on construction sites, establishing a foundational approach for automated safety compliance monitoring.
The researcher introduced a PID controller approach for the stochastic optimization of deep networks, a method published in CVPR 2018 that has garnered significant independent academic attention.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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