460 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- National Academy of Sciences of UkraineUA46 papers
- Bogolyubov Institute for Theoretical PhysicsUA36 papers
- Institute of PhysicsPL31 papers
- Taras Shevchenko National University of KyivUA21 papers
- Institute of MagnetismUA16 papers
- Institute for Information RecordingUA13 papers
- Clarkson UniversityUS12 papers
- FZU ‒ Institute of Physics of the Academy of Sciences of the Czech RepublicCZ12 papers
- Institute of MathematicsPL12 papers
- Frantsevich Institute for Problems in Materials ScienceUA11 papers
- Institute for Nuclear ResearchRU9 papers
- Johannes Gutenberg University MainzDE8 papers
5 papers · 2 filters
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…
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…
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…