23 citations · 68 across the 8 of their papers we have counts for
8 papers
Batch Size Influence on Performance of Graphic and Tensor Processing Units during Training and Inference Phases
Yuriy Kochura, Yuri Gordienko, Vlad Taran +4
The impact of the maximally possible batch size (for the better runtime) on performance of graphic processing units (GPU) and tensor processing units (TPU) during training and infe…
Capsule Deep Neural Network for Recognition of Historical Graffiti Handwriting
Nikita Gordienko, Yuriy Kochura, Vlad Taran +3
Automatic recognition of the historical letters (XI-XVIII centuries) carved on the stoned walls of St.Sophia cathedral in Kyiv (Ukraine) was demonstrated by means of capsule deep l…
Open Source Dataset and Machine Learning Techniques for Automatic Recognition of Historical Graffiti
Nikita Gordienko, Peng Gang, Yuri Gordienko +4
Machine learning techniques are presented for automatic recognition of the historical letters (XI-XVIII centuries) carved on the stoned walls of St.Sophia cathedral in Kyiv (Ukrain…
Parallel Statistical and Machine Learning Methods for Estimation of Physical Load
Sergii Stirenko, Gang Peng, Wei Zeng +4
Several statistical and machine learning methods are proposed to estimate the type and intensity of physical load and accumulated fatigue . They are based on the statistical analys…
Gamification for Education of the Digitally Native Generation by Means of Virtual Reality, Augmented Reality, Machine Learning, and Brain-Computing Interfaces in Museums
Olga Barkova, Natalia Pysarevska, Oleg Allenin +7
Particularly close attention is being paid today among researchers in social science disciplines to aspects of learning in the digital age, especially for the Digitally Native Gene…
Performance Evaluation of Deep Learning Networks for Semantic Segmentation of Traffic Stereo-Pair Images
Vlad Taran, Nikita Gordienko, Yuriy Kochura +4
Semantic image segmentation is one the most demanding task, especially for analysis of traffic conditions for self-driving cars. Here the results of application of several deep lea…
Deep Learning for Fatigue Estimation on the Basis of Multimodal Human-Machine Interactions
Yuri Gordienko, Sergii Stirenko, Yuriy Kochura +3
The new method is proposed to monitor the level of current physical load and accumulated fatigue by several objective and subjective characteristics. It was applied to the dataset…
Multi-Parametric Statistical Method for Estimation of Accumulated Fatigue by Sensors in Ordinary Gadgets
Nikita Gordienko
The new method is proposed to monitor the level of currently accumulated fatigue and estimate it by the several statistical methods. The experimental software application was devel…