Brian Dolhansky
Impact in
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- Digital Media Forensic Detection
- Generative Adversarial Networks and Image Synthesis
- Face recognition and analysis
- Advanced Image Processing Techniques
- Advanced Steganography and Watermarking Techniques
Papers in
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- Music Technology and Sound Studies 3
- Generative Adversarial Networks and Image Synthesis 2
- Digital Media Forensic Detection 2
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- Adversarial Robustness in Machine Learning 3
- Imbalanced Data Classification Techniques 1
- Co-authors
- Joanna Bitton (4 shared papers)Cristian Canton-Ferrer (1 shared paper)Menglin Wang (1 shared paper)Caner Hazırbaş (2 shared papers)Albert Gordo (2 shared papers)Jacqueline Pan (2 shared papers)Cristian Canton Ferrer (3 shared papers)Jeff Bilmes (1 shared paper)
- Journals
- IEEE Transactions on Biometrics Behavior and Identity Science (1 paper)Lecture notes in computer science (1 paper)arXiv (Cornell University) (1 paper)Neural Information Processing Systems (1 paper)
- Partner nations
- United StatesIsrael
In The Last Decade
Brian Dolhansky
8 papers receiving 220 citations
Peers
Comparison fields: 5 of 51
- Computer Vision and Pattern Recognition 165
- Signal Processing 30
- Artificial Intelligence 80
- Health Informatics 3
- Safety Research 11
Countries citing papers authored by Brian Dolhansky
This map shows the geographic impact of Brian Dolhansky'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 Brian Dolhansky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian Dolhansky more than expected).
Fields of papers citing papers by Brian Dolhansky
This network shows the impact of papers produced by Brian Dolhansky. 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 Brian Dolhansky. The network helps show where Brian Dolhansky may publish in the future.
Co-authors
The 18 scholars most cited alongside Brian Dolhansky, 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 | The DeepFake Detection Challenge Dataset | 2020 | 130 |
| 2 | 2021 | 45 | |
| 3 | 2021 | 21 | |
| 4 | 2011 | 12 | |
| 5 | Deep Submodular Functions: Definitions and Learning | 2016 | 10 |
| 6 | 2021 | 10 | |
| 7 | Relating Perceptual and Feature Space Invariances in Music Emotion Recognition | 2012 | 4 |
| 8 | 2021 | 3 | |
| 9 | 2013 | 0 |
About Brian Dolhansky
Brian Dolhansky is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Safety Research and Cognitive Neuroscience, having authored 9 papers that have together received 235 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (3 papers), Music Technology and Sound Studies (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Music and Audio Processing (2 papers), Digital Media Forensic Detection (2 papers), Speech and Audio Processing (2 papers), Ethics and Social Impacts of AI (2 papers) and Imbalanced Data Classification Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (165 citations), Signal Processing (30 citations), Artificial Intelligence (80 citations), Health Informatics (3 citations) and Safety Research (11 citations). Brian Dolhansky has collaborated with scholars based in United States and Israel. Frequent co-authors include Joanna Bitton, Cristian Canton-Ferrer, Menglin Wang, Caner Hazırbaş, Albert Gordo, Jacqueline Pan, Cristian Canton Ferrer, Jeff Bilmes, Farinaz Koushanfar and Julian McAuley. Their work appears in journals such as IEEE Transactions on Biometrics Behavior and Identity Science, Lecture notes in computer science, arXiv (Cornell University) and 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.