Daniel E. Worrall
Impact in
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- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Medical Image Segmentation Techniques
- Image Retrieval and Classification Techniques
Papers in
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- Advanced Image and Video Retrieval Techniques 2
- Advanced Neural Network Applications 2
- Multimodal Machine Learning Applications 1
- Advanced Vision and Imaging 1
- Generative Adversarial Networks and Image Synthesis 1
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- Anomaly Detection Techniques and Applications 2
- Advanced Clustering Algorithms Research 1
- Co-authors
- Stephan J. Garbin (1 shared paper)Daniyar Turmukhambetov (1 shared paper)Gabriel Brostow (2 shared papers)Max Welling (2 shared papers)Aurobrata Ghosh (1 shared paper)Francesco Grussu (1 shared paper)Ryutaro Tanno (1 shared paper)Enrico Kaden (1 shared paper)
- Journals
- NeuroImage (1 paper)Scientific Reports (1 paper)UCL Discovery (University College London) (1 paper)UvA-DARE (University of Amsterdam) (3 papers)
- Partner nations
- NetherlandsUnited KingdomGermany
In The Last Decade
Daniel E. Worrall
7 papers receiving 396 citations
Peers
Comparison fields: 5 of 90
- Computer Vision and Pattern Recognition 220
- Health Informatics 8
- Media Technology 35
- Artificial Intelligence 126
- Computational Mathematics 2
Countries citing papers authored by Daniel E. Worrall
This map shows the geographic impact of Daniel E. Worrall'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 Daniel E. Worrall with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel E. Worrall more than expected).
Fields of papers citing papers by Daniel E. Worrall
This network shows the impact of papers produced by Daniel E. Worrall. 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 Daniel E. Worrall. The network helps show where Daniel E. Worrall may publish in the future.
Co-authors
The 22 scholars most cited alongside Daniel E. Worrall, 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 | 2017 | 286 | |
| 2 | 2020 | 68 | |
| 3 | 2022 | 29 | |
| 4 | Deep Scale-spaces: Equivariance Over Scale | 2019 | 15 |
| 5 | SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks | 2020 | 14 |
| 6 | Virtual Adversarial Ladder Networks For Semi-supervised Learning | 2017 | 1 |
| 7 | 2019 | 1 |
About Daniel E. Worrall
Daniel E. Worrall is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Infectious Diseases, Statistical and Nonlinear Physics and Epidemiology, having authored 7 papers that have together received 414 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Advanced Neural Network Applications (2 papers), Multimodal Machine Learning Applications (1 paper), Advanced Clustering Algorithms Research (1 paper), Advanced Vision and Imaging (1 paper), Advanced Neuroimaging Techniques and Applications (1 paper) and Generative Adversarial Networks and Image Synthesis (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (220 citations), Health Informatics (8 citations), Media Technology (35 citations), Artificial Intelligence (126 citations) and Computational Mathematics (2 citations). Daniel E. Worrall has collaborated with scholars based in Netherlands, United Kingdom and Germany. Frequent co-authors include Stephan J. Garbin, Daniyar Turmukhambetov, Gabriel Brostow, Max Welling, Aurobrata Ghosh, Francesco Grussu, Ryutaro Tanno, Enrico Kaden, Alberto Bizzi and Stamatios N. Sotiropoulos. Their work appears in journals such as NeuroImage, Scientific Reports, UCL Discovery (University College London) and UvA-DARE (University of Amsterdam).
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.