Amit Aides

903 citations
14 papers · 496 indexed · h-index 9

Impact in

Papers in

Journals
Optics Express (1 paper)Surgical Endoscopy (1 paper)Gastrointestinal Endoscopy (1 paper)SHILAP Revista de lepidopterología (1 paper)2022 26th International Conference on Pattern Recognition (ICPR) (1 paper)

In The Last Decade

Amit Aides

13 papers receiving 486 citations

Peers

Amit Aides
Comparison fields: 5 of 60
  • Computer Vision and Pattern Recognition 280
  • Media Technology 65
  • Health Informatics 10
  • Artificial Intelligence 232
  • Computer Graphics and Computer-Aided Design 19
Replace Itsuo Kumazawa with:
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Amit Aides relative to Itsuo Kumazawa Japan Itsuo Kumazawa's profile →
Citations per field
00.5×1.5×2.2×
Itsuo Kumazawa · 1×
Citations per year

Countries citing papers authored by Amit Aides

Since Specialization
Citations

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

Fields of papers citing papers by Amit Aides

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Amit Aides, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Amit Aides Line = papers co-authored together Amit Aides links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 202234
2 20221
3 202118
4 202015
5 201978
6 20193
7 2019245
8 20181
9 20181
10 201618
11 20164
12 201547
13 201320
14 201111

About Amit Aides

Amit Aides is a scholar working on Instrumentation, Computer Vision and Pattern Recognition, Global and Planetary Change, Media Technology and Radiology, Nuclear Medicine and Imaging, having authored 14 papers that have together received 496 indexed citations. Recurring topics across this work include Atmospheric aerosols and clouds (5 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Colorectal Cancer Screening and Detection (2 papers), Advanced Optical Sensing Technologies (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Optical Imaging and Spectroscopy Techniques (2 papers), COVID-19 diagnosis using AI (1 paper) and Advanced Image Fusion Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (280 citations), Media Technology (65 citations), Health Informatics (10 citations), Artificial Intelligence (232 citations) and Computer Graphics and Computer-Aided Design (19 citations). Amit Aides has collaborated with scholars based in Israel, United States and Germany. Frequent co-authors include Joseph Shtok, Raja Giryes, Alex Bronstein, Leonid Karlinsky, Sivan Harary, Rogério Feris, Eli Schwartz, Yoav Y. Schechner, Aviad Levis and Anthony B. Davis. Their work appears in journals such as Optics Express, Surgical Endoscopy, Gastrointestinal Endoscopy, SHILAP Revista de lepidopterología and 2022 26th International Conference on Pattern Recognition (ICPR).

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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