Tal Ridnik

About

Tal Ridnik is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiation. According to data from OpenAlex, Tal Ridnik has authored 11 papers receiving a total of 412 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 4 papers in Radiation. Recurrent topics in Tal Ridnik’s work include Advanced Neural Network Applications (4 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Nuclear Physics and Applications (4 papers). Tal Ridnik is often cited by papers focused on Advanced Neural Network Applications (4 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Nuclear Physics and Applications (4 papers). Tal Ridnik collaborates with scholars based in Cayman Islands, China and Israel. Tal Ridnik's co-authors include Asaf Noy, Itamar Friedman, Emanuel Ben-Baruch, Lihi Zelnik‐Manor, Nadav Zamir, Matan Protter, Avi Ben-Cohen, Rong Jin, Hanania Ettedgui and Nadav Zamir and has published in prestigious journals such as Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, Nuclear Science and Engineering and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Co-authorship network of co-authors of Tal Ridnik i

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Fields of papers citing papers by Tal Ridnik

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tal Ridnik. 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 Tal Ridnik. The network helps show where Tal Ridnik may publish in the future.

Countries citing papers authored by Tal Ridnik

Since Specialization

Citations

This map shows the geographic impact of Tal Ridnik'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 Tal Ridnik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tal Ridnik more than expected).

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.

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