Learning-based image super-resolution using weight coefficients of synaptic connections. - Ivan Izonin; Roman Tkachenko; Dmytro Peleshko; Taras Rak; Danylo Batyuk (CSIT, 2015)

A digital watermarking scheme based on autoassociative neural networks of the geometric transformations model. - Yurii Tsymbal; Roman Tkachenko (DSMP, 2016)

Classification of Imbalanced Classes Using the Committee of Neural Networks. - Anastasiya Doroshenko; Roman Tkachenko (CSIT (1), 2018)

Hybridization of the SGTM Neural-Like Structure Through Inputs Polynomial Extension. - Pavlo Vitynskyi; Roman Tkachenko; Ivan Izonin; Hakan Kutucu (DSMP, 2018)

Identification of IT Sector Stakeholder's Requirements to Masters Program in Information System in Lviv Region. - Ihor Oleksiv; Ivan Izonin; Viktoriya Kharchuk; Roman Tkachenko; Anastasiia Doroshenko (ICTERI, 2018)

Non-iterative Neural-like Predictor for Solar Energy in Libya. - Roman Tkachenko; Hakan Kutucu; Ivan Izonin; Anastasiya Doroshenko; Yurii Tsymbal (ICTERI, 2018)

Piecewise-linear Approach for Medical Insurance Costs Prediction using SGTM Neural-Like Structure. - Roman Tkachenko; Ivan Izonin; Natalia Kryvinska; Valentyna Chopyak; Nataliia Lotoshynska; Dmytro Danylyuk (IDDM, 2018)

Development of the Non-Iterative Supervised Learning Predictor Based on the Ito Decomposition and SGTM Neural-Like Structure for Managing Medical Insurance Costs. - Roman Tkachenko; Ivan Izonin; Pavlo Vitynskyi; Nataliia Lotoshynska; Olena Pavlyuk (Data, 2018)

Neural-like Methods and Hardware Structures for Real-time Data Encryption and Decryption. - Ivan Tsmots; Yurii Tsymbal; Oleksa Skorokhoda; Roman Tkachenko (CSIT (3), 2019)

An Extended-Input GRNN and its Application. - Ivan Izonin; Natalia Kryvinska; Roman Tkachenko; Khrystyna Zub; Pavlo Vitynskyi (EUSPN/ICTH, 2019)

Recovery of Incomplete IoT Sensed Data using High-Performance Extended-Input Neural-Like Structure. - Ivan Izonin; Roman Tkachenko; Natalia Kryvinska; Khrystyna Zub; Oleksandra Mishchuk; Taras Lisovych (EUSPN/ICTH, 2019)

GRNN Approach Towards Missing Data Recovery Between IoT Systems. - Ivan Izonin; Natalia Kryvinska; Pavlo Vitynskyi; Roman Tkachenko; Khrystyna Zub (INCoS, 2019)

Committee of the SGTM Neural-Like Structures with Extended Inputs for Predictive Analytics in Insurance. - Roman Tkachenko; Ivan Izonin; Michal Gregus; Pavlo Tkachenko; Ivanna Dronyuk (Innovate-Data, 2019)

SGD-Based Wiener Polynomial Approximation for Missing Data Recovery in Air Pollution Monitoring Dataset. - Ivan Izonin; Michal Gregus; Roman Tkachenko; Mykola Logoyda; Oleksandra Mishchuk; Yurii Kynash (IWANN (1), 2019)

Multiple Linear Regression Based on Coefficients Identification Using Non-iterative SGTM Neural-like Structure. - Ivan Izonin; Roman Tkachenko; Natalia Kryvinska; Pavlo Tkachenko; Michal Gregus (IWANN (1), 2019)

Committee of the Combined RBF-SGTM Neural-Like Structures for Prediction Tasks. - Roman Tkachenko; Pavlo Tkachenko; Ivan Izonin; Pavlo Vitynskyi; Natalia Kryvinska; Yurii Tsymbal (MobiWIS, 2019)

Addressing Medical Diagnostics Issues: Essential Aspects of the PNN-based Approach. - Ivan Izonin; Roman Tkachenko; Liliia Ryvak; Khrystyna Zub; Mariya Rashkevych; Olena Pavlyuk (IDDM, 2020)

An Approach towards Increasing Prediction Accuracy for the Recovery of Missing IoT Data based on the GRNN-SGTM Ensemble. - Roman Tkachenko; Ivan Izonin; Natalia Kryvinska; Ivanna Dronyuk; Khrystyna Zub (Sensors, 2020)

Input Doubling Method based on SVR with RBF kernel in Clinical Practice: Focus on Small Data. - Ivan Izonin; Roman Tkachenko; Michal Gregus; Khrystyna Zub; Nataliia Lotoshynska (ANT/EDI40, 2021)

A GRNN-based Approach towards Prediction from Small Datasets in Medical Application. - Ivan Izonin; Roman Tkachenko; Michal Gregus; Khrystyna Zub; Pavlo Tkachenko (ANT/EDI40, 2021)

An approach towards the response surface linearization via ANN-based cascade scheme for regression modeling in Healthcare. - Ivan Izonin; Roman Tkachenko (EUSPN/ICTH, 2021)

Hybrid Classifier via PNN-based Dimensionality Reduction Approach for Biomedical Engineering Task. - Ivan Izonin; Roman Tkachenko; Michal Gregus; Liliia Ryvak; Volodymyr Kulyk; Valentyna Chopyak (FNC/MobiSPC, 2021)

Experimental Evaluation of the Effectiveness of ANN-based Numerical Data Augmentation Methods for Diagnostics Tasks. - Ivan Izonin; Roman Tkachenko; Roman Pidkostelnyi; Olena Pavliuk; Viktor Khavalko; Anatoliy Batyuk (IDDM, 2021)

An Integral Software Solution of the SGTM Neural-Like Structures Implementation for Solving Different Data Mining Tasks. - Roman Tkachenko (ISDMCI, 2021)

Neuro-Fuzzy Diagnostics Systems Based on SGTM Neural-Like Structure and T-Controller. - Roman Tkachenko; Ivan Izonin; Pavlo Tkachenko (ISDMCI, 2021)

The Additive Input-Doubling Method Based on the SVR with Nonlinear Kernels: Small Data Approach. - Ivan Izonin; Roman Tkachenko; Nataliya Shakhovska; Nataliia Lotoshynska (Symmetry, 2021)

Towards Data Normalization Task for the Efficient Mining of Medical Data. - Ivan Izonin; Bohdan Ilchyshyn; Roman Tkachenko; Michal Gregus; Natalya Shakhovska; Christine Strauss (ACIT, 2022)

Hardware Components for Nonlinear Neuro-like Data Protection in Mobile Smart Systems. - Ivan Tsmots; Roman Tkachenko; Vasyl Teslyuk; Yurii Opotyak; Vasyl Rabyk (CSIT, 2022)

I-PNN: An Improved Probabilistic Neural Network for Binary Classification of Imbalanced Medical Data. - Ivan Izonin; Roman Tkachenko; Michal Gregus (DEXA (2), 2022)

SGD-Based Cascade Scheme for Higher Degrees Wiener Polynomial Approximation of Large Biomedical Datasets. - Ivan Izonin; Roman Tkachenko; Rostyslav Holoven; Kyrylo Yemets; Myroslav Havryliuk; Shishir Kumar Shandilya (Mach. Learn. Knowl. Extr., 2022)

An Approximation Cascade Scheme via Rational Fractions for Biomedical Data Analysis. - Ivan Izonin; Roman Tkachenko; Ostap Shcherbii; Oleh Berezsky; Iurii Krak; Maksym Oliinyk (CSIT, 2023)

Development of a Device on FPGA to Implement the Base Operation of Neural-like Data Encryption Using Polynomials. - Ivan Tsmots; Roman Tkachenko; Vasyl Teslyuk; Vasyl Rabyk; Yurii Opotyak (CSIT, 2023)

Machine learning for predicting energy efficiency of buildings: a small data approach. - Ivan Izonin; Roman Tkachenko; Stergios Aristoteles Mitoulis; Asaad Faramarzi; Ivan Tsmots; Danylo Mashtalir (EUSPN/ICTH, 2023)

A Hybrid Two-ML-based Classifier to Predict the Survival of Kidney Transplants One Month after Transplantation. - Ivan Izonin; Yaroslav Tolstyak; Veronika Kachmar; Roman Tkachenko; Mariya Rashkevych; Valentyna Chopyak (IDDM, 2023)

An improved ANN-based global-local approximation for small medical data analysis. - Ivan Izonin; Roman Tkachenko; Roman Bliakhar; Michal Kovác; Yevgeniy V. Bodyanskiy; Olha Chala (EAI Endorsed Trans. Pervasive Health Technol., 2023)

An Obstacle-Finding Approach for Autonomous Mobile Robots Using 2D LiDAR Data. - Lesia I. Mochurad; Yaroslav Hladun; Roman Tkachenko (Big Data Cogn. Comput., 2023)

Implementation of Neuro-like Network Defuzzifier for Mobile Platform Motion Control System. - Vasyl Teslyuk; Ivan Tsmots; Roman Tkachenko; Pavlo Tkachenko; Vasyl Rabyk; Yurii Opotyak; Oleksandr Oliinyk (COLINS (1), 2024)

Regression-based Model for Predicting Simulated vs Actual Building Performance Discrepancies. - Ivan Izonin; Roman Tkachenko; Rosana Caro; Antonio Latorre de la Fuente; Kyrylo Yemets; Stergios Aristoteles Mitoulis (EUSPN/ICTH, 2024)

An Adaptation of the Input Doubling Method for Solving Classification Tasks in Case of Small Data Processing. - Ivan Izonin; Roman Tkachenko; Myroslav Havryliuk; Michal Gregus; Pavlo Yendyk; Yaroslav Tolstyak (FNC/MobiSPC/SEIT, 2024)

An Approach Towards Reducing Training Time of the Input Doubling Method via Clustering for Middle-Sized Data Analysis. - Ivan Izonin; Roman Tkachenko; Kyrylo Yemets; Michal Gregus; Yevhen Tomashy; Iryna Pliss (FNC/MobiSPC/SEIT, 2024)

Artificial Intelligence in Medicine: Small Data Approach. - Ivan Izonin; Roman Tkachenko; Iryna Pliss; Yaroslav Tolstyak; Kyrylo Yemets; Olha Chala; Myroslav Havryliuk; Stéphane Chrétien (IDDM, 2024)

PCA-NuSVR Framework for Predicting Local and Global Indicators of Tunneling-induced Building Damage. - Ivan Izonin; Ali Gamra; Oleslav Boychuk; Jelena Ninic; Roman Tkachenko; Stergios Aristoteles Mitoulis (SMARTINDUSTRY, 2024)

A Method for Reducing Training Time of ML-Based Cascade Scheme for Large-Volume Data Analysis. - Ivan Izonin; Roman Muzyka; Roman Tkachenko; Ivanna Dronyuk; Kyrylo Yemets; Stergios Aristoteles Mitoulis (Sensors, 2024)

Artificial Intelligence for the Future of Construction. - Ivan Izonin; Roman Tkachenko; Nataliya Shakhovska; Rosana Caro; Antonio LaTorre; Stergios Aristoteles Mitoulis (SMARTINDUSTRY, 2025)

GRNN-based cascade ensemble model for non-destructive damage state identification: small data approach. - Ivan Izonin; Athanasia K. Kazantzi; Roman Tkachenko; Stergios Aristoteles Mitoulis (Eng. Comput., 2025)