Taylor Mordan
Impact in
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- Video Surveillance and Tracking Methods
- Advanced Neural Network Applications
- Human Pose and Action Recognition
- Multimodal Machine Learning Applications
- Automotive Engineering top 10%
- Autonomous Vehicle Technology and Safety
Papers in
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- Human Pose and Action Recognition 4
- Video Surveillance and Tracking Methods 4
- Advanced Neural Network Applications 3
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- Autonomous Vehicle Technology and Safety 4
- Co-authors
- Alexandre Alahi (9 shared papers)Yuejiang Liu (2 shared papers)Matthieu Cord (2 shared papers)Parth Kothari (1 shared paper)Nicolas Thome (1 shared paper)Patrick Pérez (1 shared paper)Dongxu Guo (1 shared paper)Lorenzo Seidenari (1 shared paper)
- Journals
- IEEE Transactions on Intelligent Transportation Systems (2 papers)Drones (1 paper)IEEE Transactions on Intelligent Vehicles (1 paper)International Journal of Computer Vision (1 paper)IEEE Robotics and Automation Letters (1 paper)
- Partner nations
- SwitzerlandFranceItaly
In The Last Decade
Taylor Mordan
10 papers receiving 219 citations
Peers
Comparison fields: 5 of 52
- Computer Vision and Pattern Recognition 147
- Automotive Engineering 66
- Safety, Risk, Reliability and Quality 33
- Artificial Intelligence 96
- Physical Therapy, Sports Therapy and Rehabilitation 4
Countries citing papers authored by Taylor Mordan
This map shows the geographic impact of Taylor Mordan'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 Taylor Mordan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Taylor Mordan more than expected).
Fields of papers citing papers by Taylor Mordan
This network shows the impact of papers produced by Taylor Mordan. 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 Taylor Mordan. The network helps show where Taylor Mordan may publish in the future.
Co-authors
The 13 scholars most cited alongside Taylor Mordan, 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 | TTT++: When Does Self-Supervised Test-Time Training Fail or Thrive? | 2021 | 62 |
| 2 | 2021 | 55 | |
| 3 | 2018 | 29 | |
| 4 | 2021 | 26 | |
| 5 | 2023 | 19 | |
| 6 | 2021 | 19 | |
| 7 | 2022 | 5 | |
| 8 | 2021 | 4 | |
| 9 | 2024 | 3 | |
| 10 | 2024 | 2 | |
| 11 | 2025 | 0 |
About Taylor Mordan
Taylor Mordan is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering, Artificial Intelligence, Control and Systems Engineering and Statistical and Nonlinear Physics, having authored 11 papers that have together received 224 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (4 papers), Human Pose and Action Recognition (4 papers), Anomaly Detection Techniques and Applications (4 papers), Video Surveillance and Tracking Methods (4 papers), Advanced Neural Network Applications (3 papers), Aerospace and Aviation Technology (1 paper), Human Resource Development and Performance Evaluation (1 paper) and Human Motion and Animation (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (147 citations), Automotive Engineering (66 citations), Safety, Risk, Reliability and Quality (33 citations), Artificial Intelligence (96 citations) and Physical Therapy, Sports Therapy and Rehabilitation (4 citations). Taylor Mordan has collaborated with scholars based in Switzerland, France and Italy. Frequent co-authors include Alexandre Alahi, Yuejiang Liu, Matthieu Cord, Parth Kothari, Nicolas Thome, Patrick Pérez, Dongxu Guo, Lorenzo Seidenari, Siyuan Li and Alberto Del Bimbo. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, Drones, IEEE Transactions on Intelligent Vehicles, International Journal of Computer Vision and IEEE Robotics and Automation Letters.
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.