Gal Lavee
Impact in
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- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
- Video Analysis and Summarization
- Advanced Image and Video Retrieval Techniques
- Artificial Intelligence top 10%
- Anomaly Detection Techniques and Applications
Papers in
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- Anomaly Detection Techniques and Applications 5
- Natural Language Processing Techniques 2
- Semantic Web and Ontologies 1
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- Human Pose and Action Recognition 5
- Video Analysis and Summarization 3
- Co-authors
- Michael Rudzsky (3 shared papers)Ehud Rivlin (3 shared papers)Latifur Khan (3 shared papers)Bhavani Thuraisingham (3 shared papers)Kira Radinsky (2 shared papers)Tomer Golany (1 shared paper)Elad Yom‐Tov (1 shared paper)Elisa Bertino (1 shared paper)
- Journals
- IEEE Transactions on Circuits and Systems for Video Technology (2 papers)Multimedia Tools and Applications (1 paper)Expert Systems with Applications (1 paper)Purdue e-Pubs (Purdue University System) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- IsraelUnited StatesIreland
In The Last Decade
Gal Lavee
12 papers receiving 276 citations
Peers
Comparison fields: 5 of 50
- Computer Vision and Pattern Recognition 209
- Artificial Intelligence 153
- Signal Processing 44
- Human-Computer Interaction 10
- Cardiology and Cardiovascular Medicine 39
Countries citing papers authored by Gal Lavee
This map shows the geographic impact of Gal Lavee'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 Gal Lavee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gal Lavee more than expected).
Fields of papers citing papers by Gal Lavee
This network shows the impact of papers produced by Gal Lavee. 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 Gal Lavee. The network helps show where Gal Lavee may publish in the future.
Co-authors
The 19 scholars most cited alongside Gal Lavee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 142 | |
| 2 | 2020 | 42 | |
| 3 | 2007 | 40 | |
| 4 | 2009 | 14 | |
| 5 | 2006 | 13 | |
| 6 | 2005 | 13 | |
| 7 | 2017 | 12 | |
| 8 | 2012 | 10 | |
| 9 | 2016 | 8 | |
| 10 | 2019 | 4 | |
| 11 | 2011 | 2 | |
| 12 | 2019 | 2 | |
| 13 | 2025 | 0 |
About Gal Lavee
Gal Lavee is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Sociology and Political Science, Information Systems and Signal Processing, having authored 13 papers that have together received 302 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (5 papers), Anomaly Detection Techniques and Applications (5 papers), Video Analysis and Summarization (3 papers), Natural Language Processing Techniques (2 papers), Gait Recognition and Analysis (2 papers), Digital Marketing and Social Media (2 papers), Recommender Systems and Techniques (2 papers) and Semantic Web and Ontologies (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (209 citations), Artificial Intelligence (153 citations), Signal Processing (44 citations), Human-Computer Interaction (10 citations) and Cardiology and Cardiovascular Medicine (39 citations). Gal Lavee has collaborated with scholars based in Israel, United States and Ireland. Frequent co-authors include Michael Rudzsky, Ehud Rivlin, Latifur Khan, Bhavani Thuraisingham, Kira Radinsky, Tomer Golany, Elad Yom‐Tov, Elisa Bertino, Jianping Fan and Royi Ronen. Their work appears in journals such as IEEE Transactions on Circuits and Systems for Video Technology, Multimedia Tools and Applications, Expert Systems with Applications, Purdue e-Pubs (Purdue University System) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.