N.I. Chervyakov

1.4k total citations · 1 hit paper
73 papers, 945 citations indexed

About

N.I. Chervyakov is a scholar working on Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, N.I. Chervyakov has authored 73 papers receiving a total of 945 indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Information Systems, 35 papers in Artificial Intelligence and 31 papers in Computer Vision and Pattern Recognition. Recurrent topics in N.I. Chervyakov's work include Cryptography and Residue Arithmetic (31 papers), Cryptography and Data Security (16 papers) and Cryptographic Implementations and Security (11 papers). N.I. Chervyakov is often cited by papers focused on Cryptography and Residue Arithmetic (31 papers), Cryptography and Data Security (16 papers) and Cryptographic Implementations and Security (11 papers). N.I. Chervyakov collaborates with scholars based in Russia, Mexico and Brazil. N.I. Chervyakov's co-authors include Pavel Lyakhov, Nikolay Nagornov, Maria Valueva, Georgii Valuev, Mikhail Babenko, Andrei Tchernykh, Vanessa Miranda-López, Maxim Deryabin, Jorge M. Cortés-Mendoza and Dmitrii Kaplun and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Neurocomputing.

In The Last Decade

N.I. Chervyakov

70 papers receiving 889 citations

Hit Papers

Application of the residue number system to reduce hardwa... 2020 2026 2022 2024 2020 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Application of the residue number system to reduce hardware costs of the convolutional neural network implementation
    2020 330 citations Maria Valueva, Pavel Lyakhov et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
N.I. Chervyakov Russia 15 371 354 259 209 104 73 945
Eric Ke Wang China 16 311 0.8× 345 1.0× 194 0.7× 344 1.6× 106 1.0× 54 953
Pavel Lyakhov Russia 15 305 0.8× 199 0.6× 240 0.9× 86 0.4× 154 1.5× 98 945
Lahouari Ghouti Saudi Arabia 18 376 1.0× 367 1.0× 405 1.6× 231 1.1× 85 0.8× 69 1.2k
Nawal El‐Fishawy Egypt 21 486 1.3× 216 0.6× 536 2.1× 273 1.3× 164 1.6× 131 1.5k
Bin Gu China 8 414 1.1× 89 0.3× 330 1.3× 117 0.6× 129 1.2× 10 1000
Ye Yuan China 16 429 1.2× 247 0.7× 290 1.1× 94 0.4× 47 0.5× 52 1.0k
Jian Yin China 17 382 1.0× 247 0.7× 540 2.1× 340 1.6× 87 0.8× 61 1.3k
Yilin Yan United States 10 635 1.7× 122 0.3× 352 1.4× 129 0.6× 110 1.1× 23 1.3k
Junwu Zhu China 13 187 0.5× 139 0.4× 217 0.8× 288 1.4× 61 0.6× 88 870
Samir Elmougy Egypt 17 338 0.9× 151 0.4× 235 0.9× 221 1.1× 90 0.9× 70 935

Countries citing papers authored by N.I. Chervyakov

Since Specialization
Citations

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

Fields of papers citing papers by N.I. Chervyakov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by N.I. Chervyakov. 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 N.I. Chervyakov. The network helps show where N.I. Chervyakov may publish in the future.

Co-authorship network of co-authors of N.I. Chervyakov

This figure shows the co-authorship network connecting the top 25 collaborators of N.I. Chervyakov. A scholar is included among the top collaborators of N.I. Chervyakov 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 N.I. Chervyakov. N.I. Chervyakov 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.
Babenko, Mikhail, S.J. Piestrak, N.I. Chervyakov, & Maxim Deryabin. (2021). The Study of Monotonic Core Functions and Their Use to Build RNS Number Comparators. Electronics. 10(9). 1041–1041. 1 indexed citations
2.
Chervyakov, N.I., et al.. (2020). 3D-generalization of impulse noise removal method for video data processing. Computer Optics. 44(1). 3 indexed citations
3.
Chervyakov, N.I., Pavel Lyakhov, Mikhail Babenko, et al.. (2020). A Division Algorithm in a Redundant Residue Number System Using Fractions. Applied Sciences. 10(2). 695–695. 2 indexed citations
4.
Chervyakov, N.I., et al.. (2020). EEG Neuro - processing for the development of neurointerfaces. IOP Conference Series Materials Science and Engineering. 873(1). 12003–12003. 2 indexed citations
5.
Lyakhov, Pavel, et al.. (2020). Method for Determining Skin Lesions from Images Using Neural Network. 1–4. 2 indexed citations
6.
Babenko, Mikhail, et al.. (2019). Efficient Number Comparison in the Residue Number System based on Positional Characteristics. Proceedings of the Institute for System Programming of RAS. 31(2). 187–202. 2 indexed citations
7.
Babenko, Mikhail, et al.. (2019). Efficient Number Comparison in the Residue Number System based on Positional Characteristics. SHILAP Revista de lepidopterología. 31(2). 187–202. 5 indexed citations
8.
Kaplun, Dmitrii, et al.. (2019). Hardware Implementation of Video Processing Device using Residue Number System. 701–704. 2 indexed citations
9.
10.
Chervyakov, N.I., et al.. (2019). The Threshold Method of Secret's Division Based on Redundant Modular Computing Structures. INFORMACIONNYE TEHNOLOGII. 25(9). 553–561.
11.
Chervyakov, N.I., et al.. (2018). Area-Efficient FPGA Implementation of Minimalistic Convolutional Neural Network Using Residue Number System. SHILAP Revista de lepidopterología.
12.
Chervyakov, N.I., et al.. (2018). Reliability Improvement of Information Systems by Residue Number System Code. 9(1). 81–84. 3 indexed citations
13.
Deryabin, Maxim, et al.. (2018). High Performance Parallel Computing in Residue Number System. 9(1). 62–67. 5 indexed citations
14.
15.
Chervyakov, N.I., et al.. (2018). Two methods of adaptive median filtering of impulse noise in images. Computer Optics. 42(4). 667–678. 14 indexed citations
16.
Tchernykh, Andrei, Mikhail Babenko, N.I. Chervyakov, et al.. (2018). AC-RRNS: Anti-collusion secured data sharing scheme for cloud storage. International Journal of Approximate Reasoning. 102. 60–73. 34 indexed citations
17.
Chervyakov, N.I., et al.. (2018). A new model to optimize the architecture of a fault-tolerant modular neurocomputer. Neurocomputing. 303. 37–46. 3 indexed citations
18.
Chervyakov, N.I., et al.. (2017). Modification of Asmuth-Bloom data sharing scheme using the fractal geometry method. 15(1). 7–14. 1 indexed citations
19.
Chervyakov, N.I., Amir Sabbagh Molahosseini, Pavel Lyakhov, Mikhail Babenko, & Maxim Deryabin. (2016). Residue-to-binary conversion for general moduli sets based on approximate Chinese remainder theorem. International Journal of Computer Mathematics. 94(9). 1833–1849. 37 indexed citations
20.
Chervyakov, N.I., et al.. (2016). High-speed smoothing filter in the Residue Number System. 121–126. 4 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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