Idan Schwartz

33 total papers · 535 total citations
9 papers, 210 citations indexed

About

Idan Schwartz is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Idan Schwartz has authored 9 papers receiving a total of 210 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 2 papers in Signal Processing. Recurrent topics in Idan Schwartz's work include Multimodal Machine Learning Applications (5 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Idan Schwartz is often cited by papers focused on Multimodal Machine Learning Applications (5 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Idan Schwartz collaborates with scholars based in Israel, United States and Denmark. Idan Schwartz's co-authors include Tamir Hazan, Alexander G. Schwing, Lior Wolf, Seunghak Yu, Itai Gat, Yossi Adi, Sagie Benaim, Ariel Shamir, Serge Belongie and Alex Schwing and has published in prestigious journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Research at the University of Copenhagen (University of Copenhagen) and Neural Information Processing Systems.

In The Last Decade

Idan Schwartz

9 papers receiving 203 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Idan Schwartz	167	99	18	5	4	9	210
Hyunjik Kim	90 0.5×	89 0.9×	23 1.3×	4 0.8×	2 0.5×	8	142
Nayyer Aafaq	183 1.1×	78 0.8×	18 1.0×	6 1.2×	5 1.3×	15	246
Lorenzo Pellegrini	94 0.6×	134 1.4×	10 0.6×	8 1.6×	4 1.0×	10	175
Jiannan Wu	146 0.9×	90 0.9×	10 0.6×	5 1.0×	3 0.8×	5	207
Alexander H. Liu	187 1.1×	70 0.7×	26 1.4×	3 0.6×	7 1.8×	14	246
Joanna Bitton	147 0.9×	73 0.7×	29 1.6×	8 1.6×	6 1.5×	6	202
Christian Bartz	199 1.2×	97 1.0×	12 0.7×	3 0.6×	1 0.3×	7	240
Vincent Cartillier	147 0.9×	74 0.7×	17 0.9×	4 0.8×	3 0.8×	6	167
Gunnar A. Sigurdsson	114 0.7×	90 0.9×	14 0.8×	6 1.2×	4 1.0×	11	182
Brian Dolhansky	147 0.9×	72 0.7×	28 1.6×	11 2.2×	6 1.5×	8	209

Countries citing papers authored by Idan Schwartz

Since Specialization

Citations

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

Fields of papers citing papers by Idan Schwartz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Idan Schwartz

This figure shows the co-authorship network connecting the top 25 collaborators of Idan Schwartz. A scholar is included among the top collaborators of Idan Schwartz 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 Idan Schwartz. Idan Schwartz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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