Robert E. Banfield
Impact in
- Artificial Intelligence top 5%
- Machine Learning and Data Classification
- Neural Networks and Applications
- Imbalanced Data Classification Techniques
- Anomaly Detection Techniques and Applications
- Data Stream Mining Techniques
- Evolutionary Algorithms and Applications
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- Face and Expression Recognition
Papers in
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- Data Stream Mining Techniques 6
- Machine Learning and Data Classification 5
- Anomaly Detection Techniques and Applications 4
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- Data Mining Algorithms and Applications 5
- Co-authors
- Kevin W. Bowyer (11 shared papers)Lawrence Hall (11 shared papers)W. Philip Kegelmeyer (8 shared papers)Steven A. Eschrich (2 shared papers)Richard Collins (2 shared papers)Xiao Liu (1 shared paper)
- Journals
- Information Fusion (3 papers)Data Mining and Knowledge Discovery (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)International Journal of Artificial Intelligence Tools (1 paper)Proceedings - International Conference on Pattern Recognition (2 papers)
- Partner nations
- United States
In The Last Decade
Robert E. Banfield
12 papers receiving 492 citations
Peers
Comparison fields: 5 of 96
- Artificial Intelligence 323
- Computer Vision and Pattern Recognition 104
- Signal Processing 49
- Health Information Management 19
- Information Systems 88
Countries citing papers authored by Robert E. Banfield
This map shows the geographic impact of Robert E. Banfield'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 Robert E. Banfield with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert E. Banfield more than expected).
Fields of papers citing papers by Robert E. Banfield
This network shows the impact of papers produced by Robert E. Banfield. 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 Robert E. Banfield. The network helps show where Robert E. Banfield may publish in the future.
Co-authors
The 6 scholars most cited alongside Robert E. Banfield, 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 | 2006 | 297 | |
| 2 | 2004 | 151 | |
| 3 | 2004 | 11 | |
| 4 | 2008 | 9 | |
| 5 | 2004 | 8 | |
| 6 | 2004 | 8 | |
| 7 | 2007 | 8 | |
| 8 | 2003 | 7 | |
| 9 | 2003 | 7 | |
| 10 | 2006 | 4 | |
| 11 | 2008 | 3 | |
| 12 | 2010 | 1 |
About Robert E. Banfield
Robert E. Banfield is a scholar working on Artificial Intelligence, Information Systems, Signal Processing, Molecular Biology and Computer Vision and Pattern Recognition, having authored 12 papers that have together received 514 indexed citations. Recurring topics across this work include Data Stream Mining Techniques (6 papers), Data Mining Algorithms and Applications (5 papers), Machine Learning and Data Classification (5 papers), Anomaly Detection Techniques and Applications (4 papers), Machine Learning in Bioinformatics (1 paper), Data Management and Algorithms (1 paper), Time Series Analysis and Forecasting (1 paper) and Computational Drug Discovery Methods (1 paper). The work is most often cited by research in Artificial Intelligence (323 citations), Computer Vision and Pattern Recognition (104 citations), Signal Processing (49 citations), Health Information Management (19 citations) and Information Systems (88 citations). Robert E. Banfield has collaborated with scholars based in United States. Frequent co-authors include Kevin W. Bowyer, Lawrence Hall, W. Philip Kegelmeyer, Steven A. Eschrich, Richard Collins and Xiao Liu. Their work appears in journals such as Information Fusion, Data Mining and Knowledge Discovery, IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Artificial Intelligence Tools and Proceedings - International Conference on Pattern Recognition.
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.