Ehsan Amid
Impact in
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- Industrial Vision Systems and Defect Detection
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- Image and Object Detection Techniques
- Face and Expression Recognition
- Advanced Neural Network Applications
Papers in
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- Domain Adaptation and Few-Shot Learning 2
- Machine Learning and Algorithms 2
- Imbalanced Data Classification Techniques 1
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- Face and Expression Recognition 2
- Co-authors
- Sina Rezaei Aghdam (3 shared papers)Antti Ukkonen (2 shared papers)Hamidreza Amindavar (1 shared paper)Aristides Gionis (1 shared paper)Zhaowei Zhu (1 shared paper)Yang Liu (1 shared paper)Manfred K. Warmuth (5 shared papers)Hossein Talebi (1 shared paper)
- Journals
- Lecture notes in computer science (1 paper)International Conference on Machine Learning (1 paper)Interspeech 2022 (1 paper)arXiv (Cornell University) (1 paper)Zenodo (CERN European Organization for Nuclear Research) (2 papers)
- Partner nations
- United StatesFinlandIran
In The Last Decade
Ehsan Amid
14 papers receiving 115 citations
Peers
Comparison fields: 5 of 37
- Industrial and Manufacturing Engineering 47
- Computer Vision and Pattern Recognition 57
- Computer Science Applications 11
- Artificial Intelligence 47
- Computational Mechanics 24
Countries citing papers authored by Ehsan Amid
This map shows the geographic impact of Ehsan Amid'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 Ehsan Amid with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ehsan Amid more than expected).
Fields of papers citing papers by Ehsan Amid
This network shows the impact of papers produced by Ehsan Amid. 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 Ehsan Amid. The network helps show where Ehsan Amid may publish in the future.
Co-authors
The 22 scholars most cited alongside Ehsan Amid, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 34 | |
| 2 | Multiview Triplet Embedding: Learning Attributes in Multiple Maps | 2015 | 20 |
| 3 | 2012 | 15 | |
| 4 | 2023 | 15 | |
| 5 | 2015 | 13 | |
| 6 | 2014 | 6 | |
| 7 | 2020 | 4 | |
| 8 | 2022 | 3 | |
| 9 | 2020 | 2 | |
| 10 | TRECVID 2013 Workshop, Gaithersburg, USA, November 20-22, 2013 | 2013 | 2 |
| 11 | t-Exponential Triplet Embedding. | 2016 | 1 |
| 12 | A case where a spindly two-layer linear network decisively outperforms any neural network with a fully connected input layer. | 2021 | 1 |
| 13 | Winnowing with Gradient Descent | 2020 | 1 |
| 14 | 2012 | 1 |
About Ehsan Amid
Ehsan Amid is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics, Signal Processing and Computer Science Applications, having authored 14 papers that have together received 118 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (2 papers), Surface Roughness and Optical Measurements (2 papers), Music and Audio Processing (2 papers), Industrial Vision Systems and Defect Detection (2 papers), Face and Expression Recognition (2 papers), Machine Learning and Algorithms (2 papers), Mobile Crowdsensing and Crowdsourcing (2 papers) and Imbalanced Data Classification Techniques (1 paper). The work is most often cited by research in Industrial and Manufacturing Engineering (47 citations), Computer Vision and Pattern Recognition (57 citations), Computer Science Applications (11 citations), Artificial Intelligence (47 citations) and Computational Mechanics (24 citations). Ehsan Amid has collaborated with scholars based in United States, Finland and Iran. Frequent co-authors include Sina Rezaei Aghdam, Antti Ukkonen, Hamidreza Amindavar, Aristides Gionis, Zhaowei Zhu, Yang Liu, Manfred K. Warmuth, Hossein Talebi, Peyman Milanfar and Mikko Kurimo. Their work appears in journals such as Lecture notes in computer science, International Conference on Machine Learning, Interspeech 2022, arXiv (Cornell University) and Zenodo (CERN European Organization for Nuclear Research).
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.