James Gabriel
Impact in
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- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- Advanced Vision and Imaging
- Human Pose and Action Recognition
- Advanced Image and Video Retrieval Techniques
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- Industrial Vision Systems and Defect Detection
Papers in
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- Advanced Image and Video Retrieval Techniques 2
- Advanced Neural Network Applications 2
- Multimodal Machine Learning Applications 1
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- Click Chemistry and Applications 1
- Co-authors
- Oncel Tuzel (4 shared papers)Anurag Ranjan (3 shared papers)Pavan Kumar Anasosalu Vasu (3 shared papers)Jeff Zhu (2 shared papers)Muhammed Kocabas (1 shared paper)Frederick M. MacDonnell (1 shared paper)Hadi Pouransari (1 shared paper)Fartash Faghri (1 shared paper)
- Journals
- ChemMedChem (1 paper)
- Partner nations
- United States
In The Last Decade
James Gabriel
5 papers receiving 242 citations
James Gabriel's Hit Papers
Peers
Comparison fields: 5 of 72
- Computer Vision and Pattern Recognition 124
- Industrial and Manufacturing Engineering 25
- Computer Graphics and Computer-Aided Design 6
- Media Technology 14
- Instrumentation 4
Countries citing papers authored by James Gabriel
This map shows the geographic impact of James Gabriel'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 James Gabriel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Gabriel more than expected).
Fields of papers citing papers by James Gabriel
This network shows the impact of papers produced by James Gabriel. 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 James Gabriel. The network helps show where James Gabriel may publish in the future.
Co-authors
The 9 scholars most cited alongside James Gabriel, 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 | MobileOne: An Improved One millisecond Mobile Backbone Hit paper breakdown → | 2023 | 145 |
| 2 | 2023 | 53 | |
| 3 | 2024 | 30 | |
| 4 | 2017 | 21 | |
| 5 | 2025 | 1 |
About James Gabriel
James Gabriel is a scholar working on Computer Vision and Pattern Recognition, Organic Chemistry, Computer Networks and Communications, Oncology and Computational Mechanics, having authored 5 papers that have together received 250 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (2 papers), Advanced Neural Network Applications (2 papers), Domain Adaptation and Few-Shot Learning (1 paper), COVID-19 diagnosis using AI (1 paper), 3D Shape Modeling and Analysis (1 paper), Multimodal Machine Learning Applications (1 paper), Metal complexes synthesis and properties (1 paper) and Click Chemistry and Applications (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (124 citations), Industrial and Manufacturing Engineering (25 citations), Computer Graphics and Computer-Aided Design (6 citations), Media Technology (14 citations) and Instrumentation (4 citations). James Gabriel has collaborated with scholars based in United States. Frequent co-authors include Oncel Tuzel, Anurag Ranjan, Pavan Kumar Anasosalu Vasu, Jeff Zhu, Muhammed Kocabas, Frederick M. MacDonnell, Hadi Pouransari, Fartash Faghri and Chunliang Li. Their work appears in journals such as ChemMedChem.
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.