Yali Amit
Impact in
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- Medical Image Segmentation Techniques
- Advanced Image and Video Retrieval Techniques
- Image Retrieval and Classification Techniques
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function
- EEG and Brain-Computer Interfaces
Papers in
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- Medical Image Segmentation Techniques 8
- Image Retrieval and Classification Techniques 8
- Advanced Image and Video Retrieval Techniques 7
- Image and Object Detection Techniques 6
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- Neural dynamics and brain function 14
- Co-authors
- Donald GemanUlf GrenanderNicholas G. HatsopoulosAlain TrouvéMauro PiccioniMichael I. MillerGary E. ChristensenStéphanie Allassonnière
- Journals
- Neural Computation (6 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (4 papers)Journal of Multivariate Analysis (2 papers)Journal of Neuroscience (2 papers)Journal of the American Statistical Association (2 papers)
- Partner nations
- United StatesFranceIsrael
In The Last Decade
Yali Amit
58 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 170
- Computer Vision and Pattern Recognition 1.5k
- Cognitive Neuroscience 636
- Media Technology 205
- Artificial Intelligence 740
- Statistics and Probability 182
Countries citing papers authored by Yali Amit
This map shows the geographic impact of Yali Amit'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 Yali Amit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yali Amit more than expected).
Fields of papers citing papers by Yali Amit
This network shows the impact of papers produced by Yali Amit. 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 Yali Amit. The network helps show where Yali Amit may publish in the future.
Co-authors
The 25 scholars most cited alongside Yali Amit, 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 | 2022 | 4 | |
| 2 | Generative Latent Flow: A Framework for Non-adversarial Image Generation. | 2019 | 1 |
| 3 | 2019 | 21 | |
| 4 | 2015 | 60 | |
| 5 | 2015 | 16 | |
| 6 | 2014 | 11 | |
| 7 | 2013 | 5 | |
| 8 | 2013 | 13 | |
| 9 | 2013 | 6 | |
| 10 | 2011 | 15 | |
| 11 | 2010 | 42 | |
| 12 | 2009 | 166 | |
| 13 | 2008 | 8 | |
| 14 | 2007 | 128 | |
| 15 | 2004 | 97 | |
| 16 | Computational Strategies for Model-Based Scene Interpretation | 2003 | 1 |
| 17 | 1993 | 6 | |
| 18 | 1991 | 10 | |
| 19 | 1991 | 51 | |
| 20 | 1991 | 57 |
About Yali Amit
Yali Amit is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience, Anatomy, Media Technology and Mathematical Physics, having authored 58 papers that have together received 3.1k indexed citations. Recurring topics across this work include Neural dynamics and brain function (14 papers), Advanced Memory and Neural Computing (11 papers), Medical Image Segmentation Techniques (8 papers), Image Retrieval and Classification Techniques (8 papers), Neural Networks and Applications (8 papers), Advanced Image and Video Retrieval Techniques (7 papers), Image and Object Detection Techniques (6 papers) and Bayesian Methods and Mixture Models (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Cognitive Neuroscience (636 citations), Media Technology (205 citations), Artificial Intelligence (740 citations) and Statistics and Probability (182 citations). Yali Amit has collaborated with scholars based in United States, France and Israel. Frequent co-authors include Donald Geman, Ulf Grenander, Nicholas G. Hatsopoulos, Alain Trouvé, Mauro Piccioni, Michael I. Miller, Gary E. Christensen, Stéphanie Allassonnière, Adam S. Dickey and Qingqing Xu. Their work appears in journals such as Neural Computation, IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Multivariate Analysis, Journal of Neuroscience and Journal of the American Statistical Association.
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.