collaborators

10 papers

eess.SP2026

Demodulation of chaotic signals using convolutional neural network

Mykola Kozlenko, Emrullah Demiral, Anton Yudhana

Chaotic modulation is an effective communication technique that exploits deterministic chaos to produce pseudo-random signals. A widely adopted approach involves modulation of the…

cs.CL2025

Research on a hybrid LSTM-CNN-Attention model for text-based web content classification

Mykola Kuz, Ihor Lazarovych, Mykola Kozlenko +2

This study presents a hybrid deep learning architecture that integrates LSTM, CNN, and an Attention mechanism to enhance the classification of web content based on text. Pretrained…

cs.CV2025

Application of deep learning approaches for medieval historical documents transcription

Maksym Voloshchuk, Bohdana Zarembovska, Mykola Kozlenko

Handwritten text recognition and optical character recognition solutions show excellent results with processing data of modern era, but efficiency drops with Latin documents of med…

cs.SE2025

Methods for evaluating software accessibility

Mykola Kuz, Ivan Yaremiy, Hanna Yaremii +4

The development and enhancement of methods for evaluating software accessibility is a relevant challenge in modern software engineering, as ensuring equal access to digital service…

eess.SP2025

Supervised machine learning based signal demodulation in chaotic communications

Mykola Kozlenko

A chaotic modulation scheme is an efficient wideband communication method. It utilizes the deterministic chaos to generate pseudo-random carriers. Chaotic bifurcation parameter mod…

cs.SD2025

Machine learning based animal emotion classification using audio signals

Mariia Slobodian, Mykola Kozlenko

This paper presents the machine learning approach to the automated classification of a dog's emotional state based on the processing and recognition of audio signals. It offers hel…