Andrea Vedaldi Google Scholar: h-index, Total Citations, and Citation Map
Andrea Vedaldi's h-index is 123 (278 i10-index, 135,869+ total citations across 494+ publications) according to Google Scholar as of November 2026. Andrea Vedaldi is affiliated with University of Oxford.
Andrea Vedaldi is a researcher affiliated with University of Oxford, specializing in Computer Vision, Machine Learning. Their work has been cited 135,869 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Andrea Vedaldi's Citation Metrics
Bibliometric impact based on 494 indexed publications.
- H-Index
- 123
- i10-Index
- 278
- Total Citations
- 135,869
- Citing Countries
- 92
As of November 2026.
Andrea Vedaldi has an h-index of 123 and 135,869 total citations across 494 publications, with research cited by institutions in 92 countries.
Global Impact Map
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Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
201411,079
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 Andrea Vedaldi's research
Andrea Vedaldi is a researcher in Computer Vision and Machine Learning at University of Oxford. Their work has been cited 135,869 times across 494 publications (h-index 123), according to Google Scholar.
Their most-cited work, “Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps” (2014), has accumulated 11,079 citations. Other influential works include “Deep face recognition” (2015) with 7,496 citations and “Fully-convolutional siamese networks for object tracking” (2016) with 6,188 citations.
Citations of Andrea Vedaldi'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.
