Janne Hellsten
Impact in
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- Generative Adversarial Networks and Image Synthesis
- Advanced Image Processing Techniques
- Digital Media Forensic Detection
- Advanced Vision and Imaging
- Advanced Image and Video Retrieval Techniques
- Video Analysis and Summarization
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- Computer Graphics and Visualization Techniques
Papers in
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- Generative Adversarial Networks and Image Synthesis 2
- Human Pose and Action Recognition 1
- Image Processing and 3D Reconstruction 1
- Digital Media Forensic Detection 1
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- Model Reduction and Neural Networks 1
- Co-authors
- Jaakko Lehtinen (2 shared papers)Tero Karras (2 shared papers)Samuli Laine (2 shared papers)Timo Aila (2 shared papers)Miika Aittala (2 shared papers)
- Journals
- Neural Information Processing Systems (1 paper)
- Partner nations
- United KingdomFinlandUnited States
In The Last Decade
Janne Hellsten
2 papers receiving 56 citations
Peers
Comparison fields: 5 of 20
- Computer Vision and Pattern Recognition 42
- Computer Graphics and Computer-Aided Design 7
- Health Informatics 1
- Artificial Intelligence 18
- Statistical and Nonlinear Physics 5
Countries citing papers authored by Janne Hellsten
This map shows the geographic impact of Janne Hellsten'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 Janne Hellsten with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Janne Hellsten more than expected).
Fields of papers citing papers by Janne Hellsten
This network shows the impact of papers produced by Janne Hellsten. 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 Janne Hellsten. The network helps show where Janne Hellsten may publish in the future.
Co-authors
The 5 scholars most cited alongside Janne Hellsten, 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 | Training Generative Adversarial Networks with Limited Data | 2020 | 40 |
| 2 | 2024 | 19 |
About Janne Hellsten
Janne Hellsten is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Infectious Diseases, Organic Chemistry and Surgery, having authored 2 papers that have together received 59 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (2 papers), Model Reduction and Neural Networks (1 paper), Human Pose and Action Recognition (1 paper), Image Processing and 3D Reconstruction (1 paper) and Digital Media Forensic Detection (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (42 citations), Computer Graphics and Computer-Aided Design (7 citations), Health Informatics (1 citation), Artificial Intelligence (18 citations) and Statistical and Nonlinear Physics (5 citations). Janne Hellsten has collaborated with scholars based in United Kingdom, Finland and United States. Frequent co-authors include Jaakko Lehtinen, Tero Karras, Samuli Laine, Timo Aila and Miika Aittala. Their work appears in journals such as Neural Information Processing Systems.
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.