Tom White
Impact in
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- Generative Adversarial Networks and Image Synthesis
- Advanced Image Processing Techniques
- Digital Media Forensic Detection
- Advanced Neural Network Applications
- Image and Signal Denoising Methods
- Artificial Intelligence top 1%
- Anomaly Detection Techniques and Applications
- AI in cancer detection
Papers in
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- Generative Adversarial Networks and Image Synthesis 2
- Image and Signal Denoising Methods 1
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- Color perception and design 2
- Co-authors
- Vincent Dumoulin (1 shared paper)Antonia Creswell (1 shared paper)Kai Arulkumaran (1 shared paper)Biswa Sengupta (1 shared paper)Anil A. Bharath (1 shared paper)Peter Gardner (1 shared paper)Ed Sutherland (1 shared paper)Sophie Wells (1 shared paper)
- Journals
- IEEE Computer Graphics and Applications (1 paper)IEEE Signal Processing Magazine (1 paper)Psychology and Marketing (1 paper)Color and Imaging Conference (1 paper)SSRN Electronic Journal (1 paper)
- Partner nations
- New ZealandUnited KingdomUnited States
In The Last Decade
Tom White
7 papers receiving 3.0k citations
Tom White's Hit Papers
Peers
Comparison fields: 5 of 173
- Computer Vision and Pattern Recognition 1000
- Artificial Intelligence 856
- Media Technology 221
- Signal Processing 240
- Health Informatics 25
Countries citing papers authored by Tom White
This map shows the geographic impact of Tom White'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 Tom White with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom White more than expected).
Fields of papers citing papers by Tom White
This network shows the impact of papers produced by Tom White. 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 Tom White. The network helps show where Tom White may publish in the future.
Co-authors
The 14 scholars most cited alongside Tom White, 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 | Generative Adversarial Networks: An Overview Hit paper breakdown → | 2018 | 2839 |
| 2 | 2012 | 122 | |
| 3 | 1998 | 85 | |
| 4 | Sampling Generative Networks: Notes on a Few Effective Techniques. | 2016 | 17 |
| 5 | 2010 | 3 | |
| 6 | Generating Animations by Sketching in Conceptual Space. | 2017 | 1 |
| 7 | 1998 | 1 | |
| 8 | 2020 | 0 |
About Tom White
Tom White is a scholar working on Computer Vision and Pattern Recognition, Social Psychology, Artificial Intelligence, Political Science and International Relations and Control and Systems Engineering, having authored 8 papers that have together received 3.1k indexed citations. Recurring topics across this work include Color perception and design (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Color Science and Applications (1 paper), Interactive and Immersive Displays (1 paper), Design Education and Practice (1 paper), Image and Signal Denoising Methods (1 paper), Multisensory perception and integration (1 paper) and Human Motion and Animation (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (1000 citations), Artificial Intelligence (856 citations), Media Technology (221 citations), Signal Processing (240 citations) and Health Informatics (25 citations). Tom White has collaborated with scholars based in New Zealand, United Kingdom and United States. Frequent co-authors include Vincent Dumoulin, Antonia Creswell, Kai Arulkumaran, Biswa Sengupta, Anil A. Bharath, Peter Gardner, Ed Sutherland, Sophie Wells, Joshua R. Smith and Chris Dodge. Their work appears in journals such as IEEE Computer Graphics and Applications, IEEE Signal Processing Magazine, Psychology and Marketing, Color and Imaging Conference and SSRN Electronic Journal.
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.