Emanuel Ben-Baruch is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Infectious Diseases.
According to data from OpenAlex, Emanuel Ben-Baruch has authored 3 papers receiving a total of 400 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 0 papers in Infectious Diseases. Recurrent topics in Emanuel Ben-Baruch's work include Text and Document Classification Technologies (3 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Machine Learning and Data Classification (2 papers). Emanuel Ben-Baruch is often cited by papers focused on Text and Document Classification Technologies (3 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Machine Learning and Data Classification (2 papers). Emanuel Ben-Baruch collaborates with scholars based in Cayman Islands. Emanuel Ben-Baruch's co-authors include Tal Ridnik, Asaf Noy, Lihi Zelnik‐Manor, Itamar Friedman, Matan Protter and Avi Ben-Cohen and has published in prestigious journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
In The Last Decade
Emanuel Ben-Baruch
3 papers
receiving
388 citations
Hit Papers
What are hit papers?
Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Asymmetric Loss For Multi-Label Classification
2021323 citationsTal Ridnik, Emanuel Ben-Baruch et al.2021 IEEE/CVF International Conference on Computer Vision (ICCV)profile →
Citations per field, relative to Emanuel Ben-Baruch
Emanuel Ben-Baruch · 1×
×1.0256AI
×1.0205CVPR
×1.042RNMI
×1.023SP
×1.021CCM
Citations per year, relative to Emanuel Ben-Baruch
Emanuel Ben-Baruch · 1×
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
Countries citing papers authored by Emanuel Ben-Baruch
Since
Specialization
Citations
This map shows the geographic impact of Emanuel Ben-Baruch'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 Emanuel Ben-Baruch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emanuel Ben-Baruch more than expected).
Fields of papers citing papers by Emanuel Ben-Baruch
This network shows the impact of papers produced by Emanuel Ben-Baruch. 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 Emanuel Ben-Baruch. The network helps show where Emanuel Ben-Baruch may publish in the future.
Co-authorship network of co-authors of Emanuel Ben-Baruch
This figure shows the co-authorship network connecting the top 25 collaborators of Emanuel Ben-Baruch.
A scholar is included among the top collaborators of Emanuel Ben-Baruch 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 Emanuel Ben-Baruch. Emanuel Ben-Baruch is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Emanuel Ben-Baruch, Tal Ridnik et al.
27
3
Asymmetric Loss For Multi-Label Classification breakdown →
2021 IEEE/CVF International Conference on Computer Vision (ICCV)
Tal Ridnik, Emanuel Ben-Baruch et al.
323
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.