Rami Ben‐Ari
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Media Technology top 10%
- Pulmonary and Respiratory Medicine
- Co-authors
- Sharbell HashoulNir SochenAyelet Akselrod-BallinLeonid KarlinskyJacob GoldbergerElla BarkanPavel KisilevJeremias Sulam
- Topics
- AI in cancer detection (11 papers)Advanced Vision and Imaging (7 papers)Advanced Image Processing Techniques (6 papers)
- Cited by
- Computer Vision and Pattern RecognitionRadiology, Nuclear Medicine and ImagingArtificial Intelligence
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceNeurocomputingJournal of Mathematical Imaging and Vision
- Partner nations
- Israel
In The Last Decade
Rami Ben‐Ari
26 papers receiving 317 citations
Peers
Comparison fields: 5 of 59
- Artificial Intelligence 188
- Computer Vision and Pattern Recognition 173
- Radiology, Nuclear Medicine and Imaging 157
- Media Technology 51
- Pulmonary and Respiratory Medicine 23
Countries citing papers authored by Rami Ben‐Ari
This map shows the geographic impact of Rami Ben‐Ari'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 Rami Ben‐Ari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rami Ben‐Ari more than expected).
Fields of papers citing papers by Rami Ben‐Ari
This network shows the impact of papers produced by Rami Ben‐Ari. 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 Rami Ben‐Ari. The network helps show where Rami Ben‐Ari may publish in the future.
Co-authorship network of co-authors of Rami Ben‐Ari
This figure shows the co-authorship network connecting the top 25 collaborators of Rami Ben‐Ari. A scholar is included among the top collaborators of Rami Ben‐Ari based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Rami Ben‐Ari. Rami Ben‐Ari is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 9 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 8 | |
| 6 | 7 | |
| 7 | Toward Self-Supervised Object Detection in Unlabeled Videos | 1 |
| 8 | A dual branch deep neural network for classification and detection in mammograms. | 3 |
| 9 | 10 | |
| 10 | 11 | |
| 11 | 37 | |
| 12 | 12 | |
| 13 | 28 | |
| 14 | 4 | |
| 15 | 18 | |
| 16 | 3 | |
| 17 | 9 | |
| 18 | 21 | |
| 19 | 5 | |
| 20 | 18 |
About Rami Ben‐Ari
Rami Ben‐Ari is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence, having authored 27 papers that have together received 333 indexed citations. Recurring topics across this work include AI in cancer detection (11 papers), Advanced Vision and Imaging (7 papers) and Advanced Image Processing Techniques (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (173 citations), Radiology, Nuclear Medicine and Imaging (157 citations) and Artificial Intelligence (188 citations). Rami Ben‐Ari has collaborated with scholars based in Israel. Frequent co-authors include Sharbell Hashoul, Nir Sochen, Ayelet Akselrod-Ballin, Leonid Karlinsky, Jacob Goldberger, Ella Barkan, Pavel Kisilev, Jeremias Sulam, Sharon Alpert and Tsvi Tlusty. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Neurocomputing and Journal of Mathematical Imaging and Vision.
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.