131 citations · 466 across the 23 of their papers we have counts for
23 papers
Self-supervised Model Based on Masked Autoencoders Advance CT Scans Classification
Jiashu Xu, Sergii Stirenko
The coronavirus pandemic has been going on since the year 2019, and the trend is still not abating. Therefore, it is particularly important to classify medical CT scans to assist i…
Prediction of Physical Load Level by Machine Learning Analysis of Heart Activity after Exercises
Peng Gang, Wei Zeng, Yuri Gordienko +3
The assessment of energy expenditure in real life is of great importance for monitoring the current physical state of people, especially in work, sport, elderly care, health care,…
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…
Impact of Ground Truth Annotation Quality on Performance of Semantic Image Segmentation of Traffic Conditions
Vlad Taran, Yuri Gordienko, Alexandr Rokovyi +2
Preparation of high-quality datasets for the urban scene understanding is a labor-intensive task, especially, for datasets designed for the autonomous driving applications. The app…
Impact of MQTT Based Sensor Network Architecture on Delivery Delay Time
Oleksandr Kovalchuk, Yuri Gordienko, Sergii Stirenko
The purpose of this study is to present two new architectures of the complexes of embedded systems in the context of the Internet of Things. The proposed new schemes use the MQTT p…
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…
Chest X-Ray Analysis of Tuberculosis by Deep Learning with Segmentation and Augmentation
Sergii Stirenko, Yuriy Kochura, Oleg Alienin +4
The results of chest X-ray (CXR) analysis of 2D images to get the statistically reliable predictions (availability of tuberculosis) by computer-aided diagnosis (CADx) on the basis…
Dimensionality Reduction in Deep Learning for Chest X-Ray Analysis of Lung Cancer
Yu. Gordienko, Yu. Kochura, O. Alienin +5
Efficiency of some dimensionality reduction techniques, like lung segmentation, bone shadow exclusion, and t-distributed stochastic neighbor embedding (t-SNE) for exclusion of outl…
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…
Deep Learning with Lung Segmentation and Bone Shadow Exclusion Techniques for Chest X-Ray Analysis of Lung Cancer
Yu. Gordienko, Peng Gang, Jiang Hui +5
The recent progress of computing, machine learning, and especially deep learning, for image recognition brings a meaningful effect for automatic detection of various diseases from…
Generating and Estimating Nonverbal Alphabets for Situated and Multimodal Communications
Serhii Hamotskyi, Sergii Stirenko, Yuri Gordienko +1
In this paper, we discuss the formalized approach for generating and estimating symbols (and alphabets), which can be communicated by the wide range of non-verbal means based on sp…
Music Transcription by Deep Learning with Data and "Artificial Semantic" Augmentation
Vladyslav Sarnatskyi, Vadym Ovcharenko, Mariia Tkachenko +3
In this progress paper the previous results of the single note recognition by deep learning are presented. The several ways for data augmentation and "artificial semantic" augmenta…
Performance Analysis of Open Source Machine Learning Frameworks for Various Parameters in Single-Threaded and Multi-Threaded Modes
Yuriy Kochura, Sergii Stirenko, Oleg Alienin +2
The basic features of some of the most versatile and popular open source frameworks for machine learning (TensorFlow, Deep Learning4j, and H2O) are considered and compared. Their c…
Comparative Performance Analysis of Neural Networks Architectures on H2O Platform for Various Activation Functions
Yuriy Kochura, Sergii Stirenko, Yuri Gordienko
Deep learning (deep structured learning, hierarchi- cal learning or deep machine learning) is a branch of machine learning based on a set of algorithms that attempt to model high-…
Performance Evaluation of Distributed Computing Environments with Hadoop and Spark Frameworks
Vladyslav Taran, Oleg Alienin, Sergii Stirenko +2
Recently, due to rapid development of information and communication technologies, the data are created and consumed in the avalanche way. Distributed computing create preconditions…
Automatized Generation of Alphabets of Symbols
Serhii Hamotskyi, Anis Rojbi, Sergii Stirenko +1
In this paper, we discuss the generation of symbols (and alphabets) based on specific user requirements (medium, priorities, type of information that needs to be conveyed). A frame…
Comparative Analysis of Open Source Frameworks for Machine Learning with Use Case in Single-Threaded and Multi-Threaded Modes
Yuriy Kochura, Sergii Stirenko, Anis Rojbi +3
The basic features of some of the most versatile and popular open source frameworks for machine learning (TensorFlow, Deep Learning4j, and H2O) are considered and compared. Their c…
Science Gateway for Distributed Multiscale Course Management in e-Science and e-Learning - Use Case for Study and Investigation of Functionalized Nanomaterials
Yuri Gordienko, Serhii Stirenko, Olexandr Gatsenko +1
The current tendency of human learning and teaching is targeted to development and integration of digital technologies (like cloud solutions, mobile technology, learning analytics,…
IMP Science Gateway: from the Portal to the Hub of Virtual Experimental Labs in Materials Science
Yuri Gordienko, Lev Bekenev, Olexandra Baskova +3
"Science gateway" (SG) ideology means a user-friendly intuitive interface between scientists (or scientific communities) and different software components + various distributed com…