Andrei Bursuc
Impact in
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- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Video Surveillance and Tracking Methods
- Geology top 10%
Papers in
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- Advanced Neural Network Applications 8
- Advanced Image and Video Retrieval Techniques 8
- Video Analysis and Summarization 5
- Multimodal Machine Learning Applications 4
- Image Retrieval and Classification Techniques 4
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- Adversarial Robustness in Machine Learning 5
- Domain Adaptation and Few-Shot Learning 3
- Co-authors
- Spyros Gidaris (6 shared papers)Gilles Puy (4 shared papers)Zaharia Titus (1 shared paper)Ruxandra Țapu (1 shared paper)Renaud Marlet (5 shared papers)Alexandre Boulch (4 shared papers)Patrick Pérez (7 shared papers)Matthieu Cord (1 shared paper)
In The Last Decade
Andrei Bursuc
28 papers receiving 377 citations
Peers
Comparison fields: 5 of 69
- Computer Vision and Pattern Recognition 226
- Geology 39
- Human-Computer Interaction 34
- Environmental Engineering 51
- Instrumentation 12
Countries citing papers authored by Andrei Bursuc
This map shows the geographic impact of Andrei Bursuc'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 Andrei Bursuc with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrei Bursuc more than expected).
Fields of papers citing papers by Andrei Bursuc
This network shows the impact of papers produced by Andrei Bursuc. 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 Andrei Bursuc. The network helps show where Andrei Bursuc may publish in the future.
Co-authors
The 25 scholars most cited alongside Andrei Bursuc, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 94 | |
| 2 | 2022 | 63 | |
| 3 | 2023 | 59 | |
| 4 | 2021 | 44 | |
| 5 | 2021 | 22 | |
| 6 | 2023 | 14 | |
| 7 | 2024 | 10 | |
| 8 | 2024 | 8 | |
| 9 | 2010 | 7 | |
| 10 | 2019 | 7 | |
| 11 | 2023 | 6 | |
| 12 | 2024 | 6 | |
| 13 | 2021 | 6 | |
| 14 | 2019 | 6 | |
| 15 | 2024 | 5 | |
| 16 | 2015 | 5 | |
| 17 | 2018 | 5 | |
| 18 | 2024 | 4 | |
| 19 | 2023 | 4 | |
| 20 | PLOP: Probabilistic Polynomial Objects trajectory Prediction for autonomous driving | 2020 | 3 |
About Andrei Bursuc
Andrei Bursuc is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Signal Processing and Environmental Engineering, having authored 31 papers that have together received 393 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (8 papers), Advanced Image and Video Retrieval Techniques (8 papers), Adversarial Robustness in Machine Learning (5 papers), Video Analysis and Summarization (5 papers), Robotics and Sensor-Based Localization (4 papers), Multimodal Machine Learning Applications (4 papers), Image Retrieval and Classification Techniques (4 papers) and Domain Adaptation and Few-Shot Learning (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (226 citations), Geology (39 citations), Human-Computer Interaction (34 citations), Environmental Engineering (51 citations) and Instrumentation (12 citations). Andrei Bursuc has collaborated with scholars based in France, Canada and Singapore. Frequent co-authors include Spyros Gidaris, Gilles Puy, Zaharia Titus, Ruxandra Țapu, Renaud Marlet, Alexandre Boulch, Patrick Pérez, Matthieu Cord, Nikos Komodakis and David Picard. Their work appears in journals such as IEEE Access, International Journal of Computer Vision, IEEE Transactions on Pattern Analysis and Machine Intelligence, Computer Vision and Image Understanding and Neurocomputing.
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.