C. Bayan Bruss
Impact in
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- Advanced Graph Neural Networks
- Neural Networks and Applications
- Imbalanced Data Classification Techniques
- Machine Learning and Data Classification
Papers in
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- Fuzzy Logic and Control Systems 2
- Neural Networks and Applications 2
- Advanced Graph Neural Networks 1
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- Medical Image Segmentation Techniques 1
- Image Retrieval and Classification Techniques 1
- Co-authors
- Keegan Hines (1 shared paper)Thomas Villmann (2 shared papers)Roshanak Nateghi (1 shared paper)Udo Seiffert (2 shared papers)Richard T. Serpe (1 shared paper)Frank-Michael Schleif (2 shared papers)Benjamin F. Zaitchik (1 shared paper)Marc Strickert (1 shared paper)
- Journals
- Frontiers in Environmental Science (1 paper)The European Symposium on Artificial Neural Networks (1 paper)PUB – Publications at Bielefeld University (Bielefeld University) (1 paper)
- Partner nations
- United States
In The Last Decade
C. Bayan Bruss
4 papers receiving 36 citations
Peers
Comparison fields: 5 of 39
- Artificial Intelligence 23
- Biophysics 3
- Statistical and Nonlinear Physics 6
- Water Science and Technology 5
- Computer Vision and Pattern Recognition 7
Countries citing papers authored by C. Bayan Bruss
This map shows the geographic impact of C. Bayan Bruss'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 C. Bayan Bruss with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C. Bayan Bruss more than expected).
Fields of papers citing papers by C. Bayan Bruss
This network shows the impact of papers produced by C. Bayan Bruss. 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 C. Bayan Bruss. The network helps show where C. Bayan Bruss may publish in the future.
Co-authors
The 9 scholars most cited alongside C. Bayan Bruss, 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 | 2019 | 18 | |
| 2 | 2019 | 9 | |
| 3 | Visualization of Fuzzy Information in Fuzzy-Classification for Image Segmentation using MDS | 2007 | 8 |
| 4 | Fuzzy Image Segmentation with Fuzzy Labelled Neural Gas | 2006 | 6 |
About C. Bayan Bruss
C. Bayan Bruss is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Astronomy and Astrophysics and Information Systems, having authored 4 papers that have together received 41 indexed citations. Recurring topics across this work include Fuzzy Logic and Control Systems (2 papers), Neural Networks and Applications (2 papers), Scientific Research and Discoveries (1 paper), Advanced Graph Neural Networks (1 paper), Medical Image Segmentation Techniques (1 paper), Image Retrieval and Classification Techniques (1 paper), Complex Network Analysis Techniques (1 paper) and Blockchain Technology Applications and Security (1 paper). The work is most often cited by research in Artificial Intelligence (23 citations), Biophysics (3 citations), Statistical and Nonlinear Physics (6 citations), Water Science and Technology (5 citations) and Computer Vision and Pattern Recognition (7 citations). C. Bayan Bruss has collaborated with scholars based in United States. Frequent co-authors include Keegan Hines, Thomas Villmann, Roshanak Nateghi, Udo Seiffert, Richard T. Serpe, Frank-Michael Schleif, Benjamin F. Zaitchik, Marc Strickert and Winfriede Weschke. Their work appears in journals such as Frontiers in Environmental Science, The European Symposium on Artificial Neural Networks and PUB – Publications at Bielefeld University (Bielefeld University).
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.