James R. Williamson
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Cognitive Neuroscience
- Media Technology top 10%
- Electrical and Electronic Engineering
- Co-authors
- Ennio MingollaStephen GrossbergD. MuchoneyIsao HayashiMichael H. BrillKristin J. HeatonAdam W. PotterTracey A. Brickell
- Topics
- Neural Networks and Applications (9 papers)Visual perception and processing mechanisms (6 papers)Neural dynamics and brain function (3 papers)
- Partner nations
- United StatesJapanCanada
In The Last Decade
James R. Williamson
21 papers receiving 374 citations
Peers
Comparison fields: 5 of 70
- Artificial Intelligence 236
- Computer Vision and Pattern Recognition 126
- Cognitive Neuroscience 94
- Media Technology 47
- Electrical and Electronic Engineering 43
Countries citing papers authored by James R. Williamson
This map shows the geographic impact of James R. Williamson'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 R. Williamson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James R. Williamson more than expected).
Fields of papers citing papers by James R. Williamson
This network shows the impact of papers produced by James R. Williamson. 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 R. Williamson. The network helps show where James R. Williamson may publish in the future.
Co-authorship network of co-authors of James R. Williamson
This figure shows the co-authorship network connecting the top 25 collaborators of James R. Williamson. A scholar is included among the top collaborators of James R. Williamson based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with James R. Williamson. James R. Williamson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | Student Chapters: Meeting Expectations and Providing High Quality Experiences. | 1 |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 4 | |
| 9 | 0 | |
| 10 | 2 | |
| 11 | 26 | |
| 12 | 20 | |
| 13 | 26 | |
| 14 | 216 | |
| 15 | 4 | |
| 16 | Neural networks for image processing, classification, and understanding | 1 |
| 17 | A Self-Organizing System for Classifying Complex Images: Natural Textures and Synthetic Aperture Radar | 1 |
| 18 | Comparison of Gaussian ARTMAP and the EM Algorithm | 1 |
| 19 | 79 | |
| 20 | Multi-sensor DLT intersection for SAR and optical images | 1 |
About James R. Williamson
James R. Williamson is a scholar working on Library and Information Sciences, Computer Vision and Pattern Recognition and Cognitive Neuroscience, having authored 25 papers that have together received 406 indexed citations. Recurring topics across this work include Neural Networks and Applications (9 papers), Visual perception and processing mechanisms (6 papers) and Neural dynamics and brain function (3 papers). The work is most often cited by research in Artificial Intelligence (236 citations), Computer Vision and Pattern Recognition (126 citations) and Media Technology (47 citations). James R. Williamson has collaborated with scholars based in United States, Japan and Canada. Frequent co-authors include Ennio Mingolla, Stephen Grossberg, D. Muchoney, Isao Hayashi, Michael H. Brill, Kristin J. Heaton, Adam W. Potter, Tracey A. Brickell, Jeffrey S. Palmer and Thomas F. Quatieri. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, Neural Computation and Neural Networks.
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.