Ben Fielding
Impact in
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- Face and Expression Recognition
- Advanced Neural Network Applications
- Human Pose and Action Recognition
- Artificial Intelligence top 5%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Machine Learning and Data Classification
Papers in
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- Multimodal Machine Learning Applications 2
- Advanced Neural Network Applications 2
- Digital Imaging for Blood Diseases 1
- Video Surveillance and Tracking Methods 1
- Face and Expression Recognition 1
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- Domain Adaptation and Few-Shot Learning 1
- Co-authors
- Li Zhang (5 shared papers)Chee Peng Lim (2 shared papers)Kamlesh Mistry (2 shared papers)Siew Chin Neoh (1 shared paper)Emma Anderson (1 shared paper)Yonghong Yu (1 shared paper)Tom Lawrence (1 shared paper)Li Zhang (1 shared paper)
- Journals
- IEEE Access (2 papers)IEEE Transactions on Cybernetics (1 paper)Electronics (1 paper)Adaptive Agents and Multi-Agents Systems (1 paper)
- Partner nations
- United KingdomAustraliaChina
In The Last Decade
Ben Fielding
6 papers receiving 448 citations
Ben Fielding's Hit Papers
Peers
Comparison fields: 5 of 74
- Computer Vision and Pattern Recognition 198
- Artificial Intelligence 213
- Experimental and Cognitive Psychology 62
- Signal Processing 40
- Computational Theory and Mathematics 42
Countries citing papers authored by Ben Fielding
This map shows the geographic impact of Ben Fielding'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 Ben Fielding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ben Fielding more than expected).
Fields of papers citing papers by Ben Fielding
This network shows the impact of papers produced by Ben Fielding. 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 Ben Fielding. The network helps show where Ben Fielding may publish in the future.
Co-authors
The 8 scholars most cited alongside Ben Fielding, 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 | A Micro-GA Embedded PSO Feature Selection Approach to Intelligent Facial Emotion Recognition Hit paper breakdown → | 2016 | 267 |
| 2 | 2019 | 98 | |
| 3 | 2018 | 63 | |
| 4 | 2020 | 18 | |
| 5 | 2019 | 17 | |
| 6 | 2016 | 2 |
About Ben Fielding
Ben Fielding is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Urban Studies, Oncology and Experimental and Cognitive Psychology, having authored 6 papers that have together received 465 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (2 papers), Advanced Neural Network Applications (2 papers), Domain Adaptation and Few-Shot Learning (1 paper), Digital Imaging for Blood Diseases (1 paper), Video Surveillance and Tracking Methods (1 paper), Cutaneous Melanoma Detection and Management (1 paper), Face and Expression Recognition (1 paper) and Advanced Computing and Algorithms (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (198 citations), Artificial Intelligence (213 citations), Experimental and Cognitive Psychology (62 citations), Signal Processing (40 citations) and Computational Theory and Mathematics (42 citations). Ben Fielding has collaborated with scholars based in United Kingdom, Australia and China. Frequent co-authors include Li Zhang, Chee Peng Lim, Kamlesh Mistry, Siew Chin Neoh, Emma Anderson, Yonghong Yu, Tom Lawrence and Li Zhang. Their work appears in journals such as IEEE Access, IEEE Transactions on Cybernetics, Electronics and Adaptive Agents and Multi-Agents Systems.
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.