Austin Abrams

423 citations
15 papers · 327 · h-index 9

Impact in

Papers in

    • Advanced Image and Video Retrieval Techniques 6
    • Video Surveillance and Tracking Methods 6
    • Advanced Vision and Imaging 5
    • Multimodal Machine Learning Applications 1
    • Anomaly Detection Techniques and Applications 2
    • Domain Adaptation and Few-Shot Learning 1

Austin Abrams

15 papers receiving 321 citations

Peers

Austin Abrams
Comparison fields: 5 of 66
  • Structural Biology 60
  • Computer Graphics and Computer-Aided Design 35
  • Computer Vision and Pattern Recognition 170
  • Ecological Modeling 16
  • Environmental Engineering 47
Replace Jean Pierre Cocquerez with:
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Jonas De Vylder Belgium
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Shigeru Owada Japan
Frédéric Labrosse United Kingdom
Mario Bijelic Germany
Bas Boom Netherlands
Thibaut Durand France
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Citations per field
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Citations per year

Countries citing papers authored by Austin Abrams

Since Specialization
Citations

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

Fields of papers citing papers by Austin Abrams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Austin Abrams, 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 Austin Abrams Line = papers co-authored together Austin Abrams links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 201181
2 200976
3 201250
4 202230
5 201319
6 201215
7 201011
8 201210
9 20158
10 20136
11 20105
12 20144
13 20114
14 20144
15 20114

About Austin Abrams

Austin Abrams is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Environmental Engineering and Molecular Biology, having authored 15 papers that have together received 327 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (6 papers), Video Surveillance and Tracking Methods (6 papers), Advanced Vision and Imaging (5 papers), Remote-Sensing Image Classification (2 papers), Remote Sensing and LiDAR Applications (2 papers), Anomaly Detection Techniques and Applications (2 papers), Multimodal Machine Learning Applications (1 paper) and Domain Adaptation and Few-Shot Learning (1 paper). The work is most often cited by research in Structural Biology (60 citations), Computer Graphics and Computer-Aided Design (35 citations), Computer Vision and Pattern Recognition (170 citations), Ecological Modeling (16 citations) and Environmental Engineering (47 citations). Austin Abrams has collaborated with scholars based in United States and Germany. Frequent co-authors include Robert Pless, Nathan Jacobs, Andrew D. Richardson, B. H. Braswell, Tao Ju, Matthew L. Baker, Michael P. Marsh, Wah Chiu, Ross A. Coleman and Corey F. Hryc. Their work appears in journals such as ACM Transactions on Multimedia Computing Communications and Applications, Journal of Structural Biology, Lecture notes in computer science and 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

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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