Natalia Neverova
- Computer Vision and Pattern Recognition top 5%
- Computational Mechanics top 10%
- Artificial Intelligence top 10%
- Endocrine and Autonomic Systems top 10%
- Control and Systems Engineering top 10%
- Co-authors
- Andrea VedaldiHanbyul JooJack L. FeldmanMoustapha CisséYossi AdiJoseph KeshetChristian WolfGengshan Yang
- Topics
- Human Pose and Action Recognition (8 papers)Advanced Vision and Imaging (7 papers)Thyroid Disorders and Treatments (5 papers)
- Cited by
- Computer Vision and Pattern RecognitionEndocrine and Autonomic SystemsComputer Graphics and Computer-Aided Design
- Journals
- Journal of NeuroscienceIEEE Transactions on Pattern Analysis and Machine IntelligenceThe Journal of Clinical Endocrinology & Metabolism
- Partner nations
- United StatesFranceJapan
In The Last Decade
Natalia Neverova
34 papers receiving 596 citations
Peers
Comparison fields: 5 of 93
- Computer Vision and Pattern Recognition 332
- Computational Mechanics 123
- Artificial Intelligence 106
- Endocrine and Autonomic Systems 95
- Control and Systems Engineering 64
Countries citing papers authored by Natalia Neverova
This map shows the geographic impact of Natalia Neverova'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 Natalia Neverova with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Natalia Neverova more than expected).
Fields of papers citing papers by Natalia Neverova
This network shows the impact of papers produced by Natalia Neverova. 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 Natalia Neverova. The network helps show where Natalia Neverova may publish in the future.
Co-authorship network of co-authors of Natalia Neverova
This figure shows the co-authorship network connecting the top 25 collaborators of Natalia Neverova. A scholar is included among the top collaborators of Natalia Neverova based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Natalia Neverova. Natalia Neverova is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 7 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 7 | |
| 7 | 11 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 9 | |
| 11 | Correlated Uncertainty for Learning Dense Correspondences from Noisy Labels | 14 |
| 12 | 18 | |
| 13 | Houdini: Fooling Deep Structured Visual and Speech Recognition Models with Adversarial Examples | 70 |
| 14 | 6 | |
| 15 | 5 | |
| 16 | 11 | |
| 17 | 34 | |
| 18 | 2 | |
| 19 | 2 | |
| 20 | 61 |
About Natalia Neverova
Natalia Neverova is a scholar working on Computer Vision and Pattern Recognition, Health Informatics and Human-Computer Interaction, having authored 35 papers that have together received 608 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (8 papers), Advanced Vision and Imaging (7 papers) and Thyroid Disorders and Treatments (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (332 citations), Endocrine and Autonomic Systems (95 citations) and Computer Graphics and Computer-Aided Design (45 citations). Natalia Neverova has collaborated with scholars based in United States, France and Japan. Frequent co-authors include Andrea Vedaldi, Hanbyul Joo, Jack L. Feldman, Moustapha Cissé, Yossi Adi, Joseph Keshet, Christian Wolf, Gengshan Yang, Minh Vo and Deva Ramanan. Their work appears in journals such as Journal of Neuroscience, IEEE Transactions on Pattern Analysis and Machine Intelligence and The Journal of Clinical Endocrinology & Metabolism.
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.