Anton Mitrokhin
Impact in
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- Advanced Neural Network Applications
- Advanced Vision and Imaging
- Video Surveillance and Tracking Methods
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- Advanced Memory and Neural Computing
- CCD and CMOS Imaging Sensors
- Ferroelectric and Negative Capacitance Devices
Papers in
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- Advanced Memory and Neural Computing 6
- CCD and CMOS Imaging Sensors 4
- Ferroelectric and Negative Capacitance Devices 2
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- Advanced Vision and Imaging 3
- Optical measurement and interference techniques 1
- Co-authors
- Cornelia Fermüller (7 shared papers)Yiannis Aloimonos (7 shared papers)Chethan M. Parameshwara (2 shared papers)Chengxi Ye (3 shared papers)Tobi Delbrück (1 shared paper)James A. Yorke (2 shared papers)Douglas Summers-Stay (1 shared paper)Gang Pan (1 shared paper)
- Journals
- Science Robotics (1 paper)Frontiers in Robotics and AI (1 paper)arXiv (Cornell University) (2 papers)
- Partner nations
- United StatesSwitzerlandUnited Kingdom
In The Last Decade
Anton Mitrokhin
8 papers receiving 475 citations
Peers
Comparison fields: 5 of 52
- Computer Vision and Pattern Recognition 165
- Electrical and Electronic Engineering 338
- Instrumentation 17
- Artificial Intelligence 130
- Cognitive Neuroscience 64
Countries citing papers authored by Anton Mitrokhin
This map shows the geographic impact of Anton Mitrokhin'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 Anton Mitrokhin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anton Mitrokhin more than expected).
Fields of papers citing papers by Anton Mitrokhin
This network shows the impact of papers produced by Anton Mitrokhin. 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 Anton Mitrokhin. The network helps show where Anton Mitrokhin may publish in the future.
Co-authors
The 9 scholars most cited alongside Anton Mitrokhin, 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 | 2018 | 223 | |
| 2 | 2019 | 83 | |
| 3 | 2019 | 65 | |
| 4 | 2020 | 45 | |
| 5 | 2020 | 37 | |
| 6 | Unsupervised Learning of Dense Optical Flow and Depth from Sparse Event Data. | 2018 | 18 |
| 7 | 2020 | 18 | |
| 8 | 2023 | 2 |
About Anton Mitrokhin
Anton Mitrokhin is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering and Instrumentation, having authored 8 papers that have together received 491 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (6 papers), CCD and CMOS Imaging Sensors (4 papers), Advanced Vision and Imaging (3 papers), Ferroelectric and Negative Capacitance Devices (2 papers), Robotics and Sensor-Based Localization (2 papers), Neural Networks and Reservoir Computing (2 papers), Advanced Optical Sensing Technologies (1 paper) and Optical measurement and interference techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (165 citations), Electrical and Electronic Engineering (338 citations), Instrumentation (17 citations), Artificial Intelligence (130 citations) and Cognitive Neuroscience (64 citations). Anton Mitrokhin has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Cornelia Fermüller, Yiannis Aloimonos, Chethan M. Parameshwara, Chengxi Ye, Tobi Delbrück, James A. Yorke, Douglas Summers-Stay, Gang Pan and Ashraful Islam. Their work appears in journals such as Science Robotics, Frontiers in Robotics and AI and arXiv (Cornell University).
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.