Natalia Neverova

3.0k total citations
35 papers, 608 citations indexed

About

Natalia Neverova is a scholar working on Computer Vision and Pattern Recognition, Endocrinology, Diabetes and Metabolism and Artificial Intelligence. According to data from OpenAlex, Natalia Neverova has authored 35 papers receiving a total of 608 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 6 papers in Endocrinology, Diabetes and Metabolism and 4 papers in Artificial Intelligence. Recurrent topics in Natalia Neverova's work include Human Pose and Action Recognition (8 papers), Advanced Vision and Imaging (7 papers) and Thyroid Disorders and Treatments (5 papers). Natalia Neverova is often cited by papers focused on Human Pose and Action Recognition (8 papers), Advanced Vision and Imaging (7 papers) and Thyroid Disorders and Treatments (5 papers). Natalia Neverova collaborates with scholars based in United States, France and Japan. Natalia Neverova's co-authors include Andrea Vedaldi, Hanbyul Joo, Jack L. Feldman, Yossi Adi, Moustapha Cissé, Joseph Keshet, Christian Wolf, Gengshan Yang, Minh Vo and Deva Ramanan and has published in prestigious journals such as Journal of Neuroscience, IEEE Transactions on Pattern Analysis and Machine Intelligence and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

Natalia Neverova

34 papers receiving 596 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Natalia Neverova 332 123 106 95 64 35 608
Pengcheng Xi 195 0.6× 172 1.4× 133 1.3× 6 0.1× 21 0.3× 66 737
Chan-Su Lee 658 2.0× 29 0.2× 127 1.2× 9 0.1× 128 2.0× 48 851
Ricard Delgado-Gonzalo 205 0.6× 111 0.9× 68 0.6× 6 0.1× 7 0.1× 49 863
Vinh‐Thong Ta 271 0.8× 23 0.2× 69 0.7× 9 0.1× 11 0.2× 28 606
Shu‐Yen Wan 227 0.7× 41 0.3× 42 0.4× 43 0.5× 21 0.3× 29 539
Hee-Deok Yang 246 0.7× 51 0.4× 44 0.4× 2 0.0× 69 1.1× 30 543
Yikai Wang 264 0.8× 52 0.4× 108 1.0× 33 0.5× 21 544
Bart Nabbe 532 1.6× 87 0.7× 75 0.7× 83 1.3× 14 668
Bertrand Vachon 577 1.7× 11 0.1× 105 1.0× 33 0.3× 17 0.3× 17 697
Kenji Terada 262 0.8× 5 0.0× 52 0.5× 78 0.8× 16 0.3× 100 520

Countries citing papers authored by Natalia Neverova

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
Liu, Xingchen, Jianyuan Wang, Jiali Duan, et al.. (2025). UnCommon Objects in 3D. 14102–14113. 1 indexed citations
2.
Neverova, Natalia, Shili Xu, Gentian Lluri, et al.. (2024). Invasive electrochemical impedance spectroscopy with phase delay for experimental atherosclerosis phenotyping. The FASEB Journal. 38(10). e23700–e23700. 1 indexed citations
3.
Sohn, Seo Young, Kosuke Inoue, Muhammad Tariq Bashir, et al.. (2024). Thyroid Dysfunction Risk After Iodinated Contrast Media Administration: A Prospective Longitudinal Cohort Analysis. The Journal of Clinical Endocrinology & Metabolism. 110(4). e1204–e1210. 7 indexed citations
4.
Inoue, Kosuke, Muhammad Tariq Bashir, Alberta L. Warner, et al.. (2024). Cardiac Electrical and Structural Changes after Iodinated Contrast Media Administration: A Longitudinal Cohort Analysis. Thyroid. 34(9). 1163–1170. 1 indexed citations
5.
Rocco, Ignacio, David Novotný, Andrea Vedaldi, et al.. (2023). Self-supervised Correspondence Estimation via Multiview Registration. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 1216–1225. 5 indexed citations
6.
Inoue, Kosuke, Martin L. Lee, Ramin Ebrahimi, et al.. (2022). Iodinated Contrast Administration and Risks of Thyroid Dysfunction: A Retrospective Cohort Analysis of the U.S. Veterans Health Administration System. Thyroid. 33(2). 230–238. 11 indexed citations
7.
Akiba, Yasutada, Angela M. Leung, Ramin Ebrahimi, et al.. (2022). Excess iodine exposure acutely increases salivary iodide and antimicrobial hypoiodous acid concentrations in humans. Scientific Reports. 12(1). 20935–20935. 2 indexed citations
8.
Inoue, Kosuke, Michael D. McClean, Jonathan D. Kaunitz, et al.. (2022). Iodine contrast exposure and incident COVID-19 infection. Frontiers in Medicine. 9. 1033601–1033601. 1 indexed citations
9.
Yang, Gengshan, Minh Vo, Natalia Neverova, et al.. (2022). BANMo: Building Animatable 3D Neural Models from Many Casual Videos. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2853–2863. 84 indexed citations
10.
Lu, Yi, Jenny Huang, Natalia Neverova, & Kim‐Lien Nguyen. (2021). USPIOs as Targeted Contrast Agents in Cardiovascular Magnetic Resonance Imaging. Current Cardiovascular Imaging Reports. 14(2). 9 indexed citations
11.
Neverova, Natalia, David Novotný, & Andrea Vedaldi. (2019). Correlated Uncertainty for Learning Dense Correspondences from Noisy Labels. Neural Information Processing Systems. 32. 918–926. 14 indexed citations
12.
Neverova, Natalia, et al.. (2019). Slim DensePose: Thrifty Learning From Sparse Annotations and Motion Cues. Oxford University Research Archive (ORA) (University of Oxford). 18 indexed citations
13.
Cissé, Moustapha, Yossi Adi, Natalia Neverova, & Joseph Keshet. (2017). Houdini: Fooling Deep Structured Visual and Speech Recognition Models with Adversarial Examples. Neural Information Processing Systems. 30. 6977–6987. 70 indexed citations
14.
Li, Fan, Natalia Neverova, Christian Wolf, & Graham W. Taylor. (2017). Modout: Learning Multi-Modal Architectures by Stochastic Regularization. 422–429. 6 indexed citations
15.
Neverova, Natalia, et al.. (2016). Modout: Learning to Fuse Modalities via Stochastic Regularization. 2(1). 5 indexed citations
16.
Neverova, Natalia & John R. Teerlink. (2014). Serelaxin: a potential new drug for the treatment of acute heart failure. Expert Opinion on Investigational Drugs. 23(7). 1017–1026. 11 indexed citations
17.
Neverova, Natalia, et al.. (2013). A Multi-scale Approach to Gesture Detection and Recognition. HAL (Le Centre pour la Communication Scientifique Directe). 484–491. 34 indexed citations
18.
Neverova, Natalia & Hubert Konik. (2012). Edge-based method for sharp region extraction from low depth of field images. 1–6. 2 indexed citations
19.
Neverova, Natalia, et al.. (2010). Protein kinase G‐dependent mechanisms modulate hypoglossal motoneuronal excitability and long‐term facilitation. The Journal of Physiology. 588(22). 4431–4439. 2 indexed citations
20.
Neverova, Natalia, et al.. (2007). Episodic Stimulation of α1-Adrenoreceptors Induces Protein Kinase C-Dependent Persistent Changes in Motoneuronal Excitability. Journal of Neuroscience. 27(16). 4435–4442. 61 indexed citations

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.

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