Evgeniy Bart

947 citations
29 papers · 696 · h-index 12

Impact in

Papers in

Evgeniy Bart

28 papers receiving 642 citations

Peers

Evgeniy Bart
Comparison fields: 5 of 83
  • Computational Mathematics 20
  • Computer Vision and Pattern Recognition 368
  • Artificial Intelligence 335
  • Signal Processing 73
  • Cognitive Neuroscience 93
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Akisato Kimura Japan
Yuchi Huang United States
Yuke Wang United States
Hayato Kobayashi Japan
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Citations per field
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Citations per year

Countries citing papers authored by Evgeniy Bart

Since Specialization
Citations

This map shows the geographic impact of Evgeniy Bart's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Evgeniy Bart with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Evgeniy Bart more than expected).

Fields of papers citing papers by Evgeniy Bart

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Evgeniy Bart. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Evgeniy Bart. The network helps show where Evgeniy Bart may publish in the future.

Co-authors

The 16 scholars most cited alongside Evgeniy Bart, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Evgeniy Bart Line = papers co-authored together Evgeniy Bart links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005138
2 201384
3 200879
4
Multi-HDP: a non parametric Bayesian model for tensor factorization
200862
5 199459
6 200444
7 200440
8 200536
9 200530
10 200823
11 201013
12 201012
13 201111
14 200810
15 200510
16 20126
17 20046
18 20115
19
Infinite State Bayes-Nets for Structured Domains
20074
20 20184

About Evgeniy Bart

Evgeniy Bart is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Cognitive Neuroscience, Media Technology and Signal Processing, having authored 29 papers that have together received 696 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (11 papers), Image Retrieval and Classification Techniques (9 papers), Image Processing Techniques and Applications (4 papers), Handwritten Text Recognition Techniques (3 papers), Advanced Vision and Imaging (3 papers), Neural dynamics and brain function (3 papers), Robotics and Sensor-Based Localization (2 papers) and Data Visualization and Analytics (2 papers). The work is most often cited by research in Computational Mathematics (20 citations), Computer Vision and Pattern Recognition (368 citations), Artificial Intelligence (335 citations), Signal Processing (73 citations) and Cognitive Neuroscience (93 citations). Evgeniy Bart has collaborated with scholars based in United States, Israel and Netherlands. Frequent co-authors include Shimon Ullman, Max Welling, Ian R. Porteous, Pietro Perona, Jay Hegdé, Vincent Chi‐Chung Cheng, Bob Price, John Hanley, Juan Liu and Hoda Eldardiry. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, PLoS ONE, Journal of Computational Neuroscience, Frontiers in Neuroscience and IBM Journal of Research and Development.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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