Steven McDonagh
Impact in
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- Computer Graphics and Visualization Techniques
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- Advanced Vision and Imaging
- Advanced Image Processing Techniques
- Image and Signal Denoising Methods
- Advanced Neural Network Applications
Papers in
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- Computer Graphics and Visualization Techniques 3
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- Advanced Vision and Imaging 8
- Advanced Image Processing Techniques 5
- Image Enhancement Techniques 3
- Multimodal Machine Learning Applications 3
- Co-authors
- Kenny MitchellBochang MoonMarkus GroßDaniel RueckertSarah ParisotMatthew F. NolanGülşen SürmeliJoseph V. Hajnal
- Journals
- IEEE Transactions on Medical Imaging (2 papers)Computer Graphics Forum (2 papers)The International Journal of High Performance Computing Applications (1 paper)Neural Networks (1 paper)ACM Transactions on Graphics (1 paper)
- Partner nations
- United KingdomSwedenUnited States
In The Last Decade
Steven McDonagh
23 papers receiving 331 citations
Peers
Comparison fields: 5 of 69
- Computer Graphics and Computer-Aided Design 49
- Computer Vision and Pattern Recognition 180
- Artificial Intelligence 101
- Pediatrics, Perinatology and Child Health 48
- Health Informatics 3
Countries citing papers authored by Steven McDonagh
This map shows the geographic impact of Steven McDonagh'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 Steven McDonagh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steven McDonagh more than expected).
Fields of papers citing papers by Steven McDonagh
This network shows the impact of papers produced by Steven McDonagh. 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 Steven McDonagh. The network helps show where Steven McDonagh may publish in the future.
Co-authors
The 25 scholars most cited alongside Steven McDonagh, 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 | 2024 | 1 | |
| 2 | 2023 | 1 | |
| 3 | 2023 | 25 | |
| 4 | 2023 | 5 | |
| 5 | 2022 | 23 | |
| 6 | 2022 | 4 | |
| 7 | Meta-Learning for Few-shot Camera-Adaptive Color Constancy. | 2018 | 1 |
| 8 | Unsupervised Lesion Detection in Brain CT using Bayesian Convolutional Autoencoders | 2018 | 31 |
| 9 | 2018 | 54 | |
| 10 | 2017 | 5 | |
| 11 | 2017 | 2 | |
| 12 | 2017 | 29 | |
| 13 | 2016 | 46 | |
| 14 | 2016 | 11 | |
| 15 | 2015 | 37 | |
| 16 | 2015 | 14 | |
| 17 | 2014 | 2 | |
| 18 | 2013 | 15 | |
| 19 | Simultaneous registration of multi-view range images with adaptive kernel density estimation | 2013 | 10 |
| 20 | Using 3D information for classification of non-melanoma skin lesions | 2008 | 8 |
About Steven McDonagh
Steven McDonagh is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Instrumentation, Radiology, Nuclear Medicine and Imaging and Developmental Neuroscience, having authored 23 papers that have together received 345 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (8 papers), Advanced Image Processing Techniques (5 papers), Domain Adaptation and Few-Shot Learning (5 papers), Computer Graphics and Visualization Techniques (3 papers), Image Enhancement Techniques (3 papers), Multimodal Machine Learning Applications (3 papers), Robotics and Sensor-Based Localization (3 papers) and COVID-19 diagnosis using AI (3 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (49 citations), Computer Vision and Pattern Recognition (180 citations), Artificial Intelligence (101 citations), Pediatrics, Perinatology and Child Health (48 citations) and Health Informatics (3 citations). Steven McDonagh has collaborated with scholars based in United Kingdom, Sweden and United States. Frequent co-authors include Kenny Mitchell, Bochang Moon, Markus Groß, Daniel Rueckert, Sarah Parisot, Matthew F. Nolan, Gülşen Sürmeli, Joseph V. Hajnal, Mary Rutherford and Amir Alansary. Their work appears in journals such as IEEE Transactions on Medical Imaging, Computer Graphics Forum, The International Journal of High Performance Computing Applications, Neural Networks and ACM Transactions on Graphics.
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.