Area-Efficient FPGA Implementation of Minimalistic Convolutional Neural Network Using Residue Number System. - Nikolay I. Chervyakov; Pavel Alekseevich Lyakhov; Maria V. Valueva; Georgii V. Valuev; Dmitrii I. Kaplun; George A. Efimenko; Denis V. Gnezdilov (FRUCT, 2018)

High-Performance Digital Filtering on Truncated Multiply-Accumulate Units in the Residue Number System. - Pavel Alekseevich Lyakhov; Maria V. Valueva; Georgii V. Valuev; Nikolay N. Nagornov (IEEE Access, 2020)

Residue Number System-Based Solution for Reducing the Hardware Cost of a Convolutional Neural Network. - Nikolay I. Chervyakov; Pavel Alekseevich Lyakhov; Maxim Anatolievich Deryabin; N. N. Nagornov; Maria V. Valueva; Georgii V. Valuev (Neurocomputing, 2020)

Application of the residue number system to reduce hardware costs of the convolutional neural network implementation. - Maria V. Valueva; N. N. Nagornov; Pavel Alekseevich Lyakhov; Georgii V. Valuev; Nikolay I. Chervyakov (Math. Comput. Simul., 2020)

Single Image Super-Resolution Method Based on Bilinear Interpolation and U-Net Combination. - Pavel Alekseevich Lyakhov; Georgii V. Valuev; Maria V. Valueva; Dmitry I. Kaplun; Aleksandr Sinitca (MECO, 2021)

Digital Filter Architecture With Calculations in the Residue Number System by Winograd Method F (2 × 2, 2 × 2). - Maria V. Valueva; Pavel Alekseevich Lyakhov; Georgii V. Valuev; Nikolay N. Nagornov (IEEE Access, 2021)

SNS-Based Secret Sharing Scheme for Security of Smart City Communication Systems. - Andrei Gladkov; Egor M. Shiriaev; Andrei Tchernykh; Maxim Deryabin; Ekaterina Bezuglova; Georgii V. Valuev; Mikhail G. Babenko (ICSC-Cities, 2022)

Method for Convolutional Neural Network Hardware Implementation Based on a Residue Number System. - Maria V. Valueva; Georgii V. Valuev; Mikhail G. Babenko; Andrei Tchernykh; Jorge M. Cortés-Mendoza (Program. Comput. Softw., 2022)

Digital Filter Architecture Based on Modified Winograd Method F(2× 2, 5× 5) and Residue Number System. - Georgii V. Valuev; Maria V. Valueva; Mikhail G. Babenko; Andrei Tchernykh (IEEE Access, 2023)

A Comparative Study of Secure Outsourced Matrix Multiplication Based on Homomorphic Encryption. - Mikhail G. Babenko; Elena Golimblevskaia; Andrei Tchernykh; Egor M. Shiriaev; Tatiana Ermakova; Luis Bernardo Pulido-Gaytan; Georgii V. Valuev; Arutyun Avetisyan; Lana A. Gagloeva (Big Data Cogn. Comput., 2023)