Matthew Boonstra
Impact in
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- Video Surveillance and Tracking Methods
- Advanced Image and Video Retrieval Techniques
- Human Pose and Action Recognition
- Advanced Vision and Imaging
- Video Analysis and Summarization
- Advanced Neural Network Applications
- Media Technology top 10%
Papers in
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- Advanced Image and Video Retrieval Techniques 2
- Video Surveillance and Tracking Methods 2
- Face and Expression Recognition 1
- Face recognition and analysis 1
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- Biomedical Text Mining and Ontologies 1
- Co-authors
- Padmanabhan Soundararajan (2 shared papers)Rangachar Kasturi (2 shared papers)V. Manohar (1 shared paper)Viktoria Korzhova (1 shared paper)Jing Zhang (1 shared paper)Reid Christian Bowers (1 shared paper)D. Goldgof (1 shared paper)John S. Garofolo (1 shared paper)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (1 paper)Figshare (1 paper)
- Partner nations
- United States
In The Last Decade
Matthew Boonstra
3 papers receiving 333 citations
Peers
Comparison fields: 5 of 49
- Computer Vision and Pattern Recognition 318
- Media Technology 29
- Artificial Intelligence 68
- Safety, Risk, Reliability and Quality 19
- Automotive Engineering 24
Countries citing papers authored by Matthew Boonstra
This map shows the geographic impact of Matthew Boonstra'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 Matthew Boonstra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Boonstra more than expected).
Fields of papers citing papers by Matthew Boonstra
This network shows the impact of papers produced by Matthew Boonstra. 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 Matthew Boonstra. The network helps show where Matthew Boonstra may publish in the future.
Co-authors
The 12 scholars most cited alongside Matthew Boonstra, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
About Matthew Boonstra
Matthew Boonstra is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology, Artificial Intelligence, Statistics and Probability and Infectious Diseases, having authored 3 papers that have together received 354 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (2 papers), Video Surveillance and Tracking Methods (2 papers), Face and Expression Recognition (1 paper), Biomedical Text Mining and Ontologies (1 paper), Statistical Methods in Clinical Trials (1 paper), Face recognition and analysis (1 paper) and AI-based Problem Solving and Planning (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (318 citations), Media Technology (29 citations), Artificial Intelligence (68 citations), Safety, Risk, Reliability and Quality (19 citations) and Automotive Engineering (24 citations). Matthew Boonstra has collaborated with scholars based in United States. Frequent co-authors include Padmanabhan Soundararajan, Rangachar Kasturi, V. Manohar, Viktoria Korzhova, Jing Zhang, Reid Christian Bowers, D. Goldgof, John S. Garofolo, Dmitry B. Goldgof and Eugene Fink. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE and Figshare.
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.