Eric Zavesky

602 citations
25 papers · 438 indexed · h-index 11
Topics
Video Analysis and Summarization (13 papers)Advanced Image and Video Retrieval Techniques (11 papers)Image Retrieval and Classification Techniques (8 papers)
Journals
IEEE Internet ComputingRare & Special e-Zone (The Hong Kong University of Science and Technology)arXiv (Cornell University)
Partner nations
United StatesItalyFrance

In The Last Decade

Eric Zavesky

25 papers receiving 412 citations

Peers

Eric Zavesky
Comparison fields: 5 of 50
  • Computer Vision and Pattern Recognition 359
  • Artificial Intelligence 163
  • Signal Processing 58
  • Information Systems 25
  • Sociology and Political Science 23
Replace Sina Samangooei with:
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Xindi Shang Singapore
Peipeng Yu China
Noel Murphy Ireland
Amirhossein Habibian Netherlands
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Citations per field
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Citations per year

Countries citing papers authored by Eric Zavesky

Since Specialization
Citations

This map shows the geographic impact of Eric Zavesky'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 Eric Zavesky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Zavesky more than expected).

Fields of papers citing papers by Eric Zavesky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric Zavesky. 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 Eric Zavesky. The network helps show where Eric Zavesky may publish in the future.

Co-authorship network of co-authors of Eric Zavesky

This figure shows the co-authorship network connecting the top 25 collaborators of Eric Zavesky. A scholar is included among the top collaborators of Eric Zavesky based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Eric Zavesky. Eric Zavesky is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 3
3 2
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Autonomous Model Management via Reinforcement Learning.
1
5 34
6
AT&T Research at TRECVID 2013 : Surveillance Event Detection
5
7 1
8 1
9 6
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Columbia University/VIREO-CityU/IRIT TRECVID2008 High-Level Feature Extraction and Interactive Video Search
51
11 3
12 11
13 113
14 22
15 21
16 10
17 19
18 12
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AT&T RESEARCH AT TRECVID 2007
18
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Columbia University TRECVID-2005 Video Search and High-Level Feature Extraction.
86

About Eric Zavesky

Eric Zavesky is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence, having authored 25 papers that have together received 438 indexed citations. Recurring topics across this work include Video Analysis and Summarization (13 papers), Advanced Image and Video Retrieval Techniques (11 papers) and Image Retrieval and Classification Techniques (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (359 citations), Signal Processing (58 citations) and Artificial Intelligence (163 citations). Eric Zavesky has collaborated with scholars based in United States, Italy and France. Frequent co-authors include Shih‐Fu Chang, Akira Yanagawa, Lyndon S. Kennedy, Winston H. Hsu, David Gibbon, Behzad Shahraray, Zhu Liu, Yu–Gang Jiang, Junfeng He and Elie Khoury. Their work appears in journals such as IEEE Internet Computing, Rare & Special e-Zone (The Hong Kong University of Science and Technology) and arXiv (Cornell University).

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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