Vassili Kovalev

151 total papers · 5.2k total citations
59 papers, 825 citations indexed

About

Vassili Kovalev is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Vassili Kovalev has authored 59 papers receiving a total of 825 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Computer Vision and Pattern Recognition, 18 papers in Artificial Intelligence and 17 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Vassili Kovalev's work include AI in cancer detection (14 papers), Medical Image Segmentation Techniques (14 papers) and Radiomics and Machine Learning in Medical Imaging (10 papers). Vassili Kovalev is often cited by papers focused on AI in cancer detection (14 papers), Medical Image Segmentation Techniques (14 papers) and Radiomics and Machine Learning in Medical Imaging (10 papers). Vassili Kovalev collaborates with scholars based in Belarus, United Kingdom and Germany. Vassili Kovalev's co-authors include Frithjof Kruggel, D. Yves von Cramon, Μαρία Πέτρου, H.-J. Gertz, M. Petrou, Mehdi Alilou, Alexander Kalinovsky, Achim Köhler, Volha Shapaval and А. Ya. Grigoriev and has published in prestigious journals such as SHILAP Revista de lepidopterología, Biomaterials and NeuroImage.

In The Last Decade

Vassili Kovalev

51 papers receiving 775 citations

Author Peers

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

Author						Papers	Cites
Vassili Kovalev	339	265	187	108	88	59	825
Kashif Rajpoot	264 0.8×	242 0.9×	222 1.2×	88 0.8×	50 0.6×	44	969
Jialin Peng	453 1.3×	387 1.5×	327 1.7×	62 0.6×	54 0.6×	40	1.0k
Shamik Tiwari	311 0.9×	187 0.7×	274 1.5×	41 0.4×	25 0.3×	74	948
Heung‐Kook Choi	334 1.0×	210 0.8×	256 1.4×	27 0.3×	57 0.6×	89	803
Dong Hye Ye	335 1.0×	246 0.9×	112 0.6×	38 0.4×	56 0.6×	53	776
Ioannis Kalatzis	192 0.6×	353 1.3×	294 1.6×	129 1.2×	67 0.8×	73	936
Yan Wang	397 1.2×	159 0.6×	275 1.5×	86 0.8×	38 0.4×	41	948
Bilge Karaçalı	387 1.1×	234 0.9×	187 1.0×	153 1.4×	56 0.6×	58	887
Christian Heinrich	164 0.5×	168 0.6×	128 0.7×	202 1.9×	20 0.2×	62	1.0k
Ricardo J. Ferrari	387 1.1×	237 0.9×	396 2.1×	27 0.3×	18 0.2×	40	756

Countries citing papers authored by Vassili Kovalev

Since Specialization

Citations

This map shows the geographic impact of Vassili Kovalev'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 Vassili Kovalev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vassili Kovalev more than expected).

Fields of papers citing papers by Vassili Kovalev

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vassili Kovalev. 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 Vassili Kovalev. The network helps show where Vassili Kovalev may publish in the future.

Co-authorship network of co-authors of Vassili Kovalev

This figure shows the co-authorship network connecting the top 25 collaborators of Vassili Kovalev. A scholar is included among the top collaborators of Vassili Kovalev 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 Vassili Kovalev. Vassili Kovalev is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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