Maxim Berman
Impact in
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- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
- Advanced Image and Video Retrieval Techniques
- Media Technology top 5%
Papers in
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- Advanced Neural Network Applications 4
- Medical Image Segmentation Techniques 1
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- Machine Learning and Algorithms 3
- Stochastic Gradient Optimization Techniques 2
- Domain Adaptation and Few-Shot Learning 1
- Adversarial Robustness in Machine Learning 1
- Co-authors
- Matthew B. Blaschko (6 shared papers)Amal Rannen Triki (3 shared papers)Frederik Maes (1 shared paper)Jeroen Bertels (1 shared paper)Tom Eelbode (1 shared paper)Dirk Vandermeulen (1 shared paper)Raf Bisschops (1 shared paper)Christos Sagonas (1 shared paper)
- Journals
- IEEE Transactions on Medical Imaging (1 paper)Lecture notes in computer science (1 paper)Lirias (KU Leuven) (3 papers)arXiv (Cornell University) (2 papers)
In The Last Decade
Maxim Berman
7 papers receiving 946 citations
Maxim Berman's Hit Papers
Peers
Comparison fields: 5 of 111
- Computer Vision and Pattern Recognition 498
- Media Technology 96
- Geology 53
- Environmental Engineering 124
- Radiology, Nuclear Medicine and Imaging 149
Countries citing papers authored by Maxim Berman
This map shows the geographic impact of Maxim Berman'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 Maxim Berman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maxim Berman more than expected).
Fields of papers citing papers by Maxim Berman
This network shows the impact of papers produced by Maxim Berman. 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 Maxim Berman. The network helps show where Maxim Berman may publish in the future.
Co-authors
The 12 scholars most cited alongside Maxim Berman, 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 | The Lovasz-Softmax Loss: A Tractable Surrogate for the Optimization of the Intersection-Over-Union Measure in Neural Networks Hit paper breakdown → | 2018 | 664 |
| 2 | Optimization for Medical Image Segmentation: Theory and Practice When Evaluating With Dice Score or Jaccard Index Hit paper breakdown → | 2020 | 276 |
| 3 | 2019 | 18 | |
| 4 | Optimization of the Jaccard index for image segmentation with the Lovász hinge. | 2017 | 10 |
| 5 | 2016 | 3 | |
| 6 | Stochastic Weighted Function Norm Regularization. | 2017 | 1 |
| 7 | 2019 | 1 | |
| 8 | 2023 | 0 |
About Maxim Berman
Maxim Berman is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mechanics, Radiology, Nuclear Medicine and Imaging and Geology, having authored 8 papers that have together received 973 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (4 papers), Machine Learning and Algorithms (3 papers), Stochastic Gradient Optimization Techniques (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Domain Adaptation and Few-Shot Learning (1 paper), Advanced X-ray and CT Imaging (1 paper), Medical Image Segmentation Techniques (1 paper) and Adversarial Robustness in Machine Learning (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (498 citations), Media Technology (96 citations), Geology (53 citations), Environmental Engineering (124 citations) and Radiology, Nuclear Medicine and Imaging (149 citations). Maxim Berman has collaborated with scholars based in Belgium, Austria and France. Frequent co-authors include Matthew B. Blaschko, Amal Rannen Triki, Frederik Maes, Jeroen Bertels, Tom Eelbode, Dirk Vandermeulen, Raf Bisschops, Christos Sagonas, Iasonas Kokkinos and Devis Tuia. Their work appears in journals such as IEEE Transactions on Medical Imaging, Lecture notes in computer science, Lirias (KU Leuven) 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.