Tom Diethe
Impact in
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- Context-Aware Activity Recognition Systems
- Face and Expression Recognition
- Advanced Image and Video Retrieval Techniques
- Artificial Intelligence top 2%
- Topic Modeling
- Anomaly Detection Techniques and Applications
- Text and Document Classification Technologies
- Domain Adaptation and Few-Shot Learning
Papers in
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- Anomaly Detection Techniques and Applications 9
- Machine Learning and Algorithms 5
- Gaussian Processes and Bayesian Inference 4
- Neural Networks and Applications 3
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- Context-Aware Activity Recognition Systems 9
- Face and Expression Recognition 4
- Co-authors
- Peter Flach (19 shared papers)Yu Chen (1 shared paper)Niall Twomey (16 shared papers)John Shawe‐Taylor (11 shared papers)Ian Craddock (5 shared papers)David R. Hardoon (4 shared papers)Dritan Kaleshi (1 shared paper)Lili Tao (1 shared paper)
- Journals
- Neurocomputing (2 papers)Drug Discovery Today (1 paper)IEEE Intelligent Systems (1 paper)Machine Learning (1 paper)Neural Computation (1 paper)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Tom Diethe
44 papers receiving 1.1k citations
Tom Diethe's Hit Papers
Peers
Comparison fields: 5 of 128
- Computer Vision and Pattern Recognition 469
- Artificial Intelligence 503
- Computational Mathematics 6
- Signal Processing 104
- Human-Computer Interaction 46
Countries citing papers authored by Tom Diethe
This map shows the geographic impact of Tom Diethe'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 Diethe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Diethe more than expected).
Fields of papers citing papers by Tom Diethe
This network shows the impact of papers produced by Tom Diethe. 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 Diethe. The network helps show where Tom Diethe may publish in the future.
Co-authors
The 25 scholars most cited alongside Tom Diethe, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence Hit paper breakdown → | 2016 | 570 |
| 2 | 2015 | 156 | |
| 3 | 2018 | 100 | |
| 4 | Multiview Fisher Discriminant Analysis | 2008 | 57 |
| 5 | Proceedings of the 7th Triennial Conference of European Society for the Cognitive Sciences of Music (ESCOM 2009) | 2009 | 55 |
| 6 | Continual Learning in Practice | 2019 | 26 |
| 7 | 2016 | 26 | |
| 8 | 2012 | 22 | |
| 9 | 2010 | 18 | |
| 10 | Active transfer learning for activity recognition | 2016 | 17 |
| 11 | 2020 | 11 | |
| 12 | 2018 | 11 | |
| 13 | Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2009 | 2009 | 9 |
| 14 | 2015 | 9 | |
| 15 | ADL™: a topic model for discovery of activities of daily living in a smart home | 2016 | 7 |
| 16 | 2019 | 7 | |
| 17 | NIPS 2008 workshop "Learning from Multiple Sources" | 2008 | 7 |
| 18 | 2015 | 7 | |
| 19 | 2011 | 7 | |
| 20 | 2023 | 6 |
About Tom Diethe
Tom Diethe is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Surgery and Computer Networks and Communications, having authored 47 papers that have together received 1.2k indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (9 papers), Anomaly Detection Techniques and Applications (9 papers), Machine Learning and Algorithms (5 papers), Time Series Analysis and Forecasting (5 papers), Face and Expression Recognition (4 papers), Gaussian Processes and Bayesian Inference (4 papers), Music and Audio Processing (4 papers) and Neural Networks and Applications (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (469 citations), Artificial Intelligence (503 citations), Computational Mathematics (6 citations), Signal Processing (104 citations) and Human-Computer Interaction (46 citations). Tom Diethe has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Peter Flach, Yu Chen, Niall Twomey, John Shawe‐Taylor, Ian Craddock, David R. Hardoon, Dritan Kaleshi, Lili Tao, Xenofon Fafoutis and Massimo Camplani. Their work appears in journals such as Neurocomputing, Drug Discovery Today, IEEE Intelligent Systems, Machine Learning and Neural Computation.
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.