Yedid Hoshen
- Artificial Intelligence top 5%
- Signal Processing top 5%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications
- Molecular Biology
- Co-authors
- Kevin WilsonRon J. WeissLior WolfBezalel PelegNiv CohenMor NitzanZoe PiranMark Silberstein
- Topics
- Anomaly Detection Techniques and Applications (6 papers)Adversarial Robustness in Machine Learning (4 papers)Domain Adaptation and Few-Shot Learning (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaNature BiotechnologyJournal of Clinical Medicine
- Partner nations
- IsraelUnited States
In The Last Decade
Yedid Hoshen
24 papers receiving 407 citations
Peers
Comparison fields: 5 of 69
- Artificial Intelligence 292
- Signal Processing 160
- Computer Vision and Pattern Recognition 92
- Computer Networks and Communications 39
- Molecular Biology 28
Countries citing papers authored by Yedid Hoshen
This map shows the geographic impact of Yedid Hoshen'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 Yedid Hoshen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yedid Hoshen more than expected).
Fields of papers citing papers by Yedid Hoshen
This network shows the impact of papers produced by Yedid Hoshen. 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 Yedid Hoshen. The network helps show where Yedid Hoshen may publish in the future.
Co-authorship network of co-authors of Yedid Hoshen
This figure shows the co-authorship network connecting the top 25 collaborators of Yedid Hoshen. A scholar is included among the top collaborators of Yedid Hoshen 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 Yedid Hoshen. Yedid Hoshen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 23 | |
| 4 | 4 | |
| 5 | 38 | |
| 6 | 38 | |
| 7 | 3 | |
| 8 | 5 | |
| 9 | PANDA - Adapting Pretrained Features for Anomaly Detection | 2 |
| 10 | 9 | |
| 11 | 12 | |
| 12 | 39 | |
| 13 | 20 | |
| 14 | 48 | |
| 15 | NAM - Unsupervised Cross-Domain Image Mapping without Cycles or GANs | 2 |
| 16 | Non-Adversarial Mapping with VAEs | 2 |
| 17 | Identifying Analogies Across Domains | 3 |
| 18 | 129 | |
| 19 | 4 | |
| 20 | 2 |
About Yedid Hoshen
Yedid Hoshen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 25 papers that have together received 429 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (6 papers), Adversarial Robustness in Machine Learning (4 papers) and Domain Adaptation and Few-Shot Learning (4 papers). The work is most often cited by research in Signal Processing (160 citations), Artificial Intelligence (292 citations) and Computer Vision and Pattern Recognition (92 citations). Yedid Hoshen has collaborated with scholars based in Israel and United States. Frequent co-authors include Kevin Wilson, Ron J. Weiss, Lior Wolf, Bezalel Peleg, Niv Cohen, Mor Nitzan, Zoe Piran, Mark Silberstein, Mohit Tiwari and Yael Vinker. Their work appears in journals such as SHILAP Revista de lepidopterología, Nature Biotechnology and Journal of Clinical Medicine.
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.