Search Results for author: Nikita Gordienko

Found 5 papers, 0 papers with code

Batch Size Influence on Performance of Graphic and Tensor Processing Units during Training and Inference Phases

no code implementations31 Dec 2018 Yuriy Kochura, Yuri Gordienko, Vlad Taran, Nikita Gordienko, Alexandr Rokovyi, Oleg Alienin, Sergii Stirenko

The significant speedup was obtained even for extremely low-scale usage of Google TPUv2 units (8 cores only) in comparison to the quite powerful GPU NVIDIA Tesla K80 card with the speedup up to 10x for training stage (without taking into account the overheads) and speedup up to 2x for prediction stage (with and without taking into account overheads).

Open Source Dataset and Machine Learning Techniques for Automatic Recognition of Historical Graffiti

no code implementations31 Aug 2018 Nikita Gordienko, Peng Gang, Yuri Gordienko, Wei Zeng, Oleg Alienin, Oleksandr Rokovyi, Sergii Stirenko

A new image dataset of these carved Glagolitic and Cyrillic letters (CGCL) was assembled and pre-processed for recognition and prediction by machine learning methods.

Data Augmentation Dimensionality Reduction

Parallel Statistical and Machine Learning Methods for Estimation of Physical Load

no code implementations14 Aug 2018 Sergii Stirenko, Gang Peng, Wei Zeng, Yuri Gordienko, Oleg Alienin, Oleksandr Rokovyi, Nikita Gordienko

Several statistical and machine learning methods are proposed to estimate the type and intensity of physical load and accumulated fatigue .

Performance Evaluation of Deep Learning Networks for Semantic Segmentation of Traffic Stereo-Pair Images

no code implementations5 Jun 2018 Vlad Taran, Nikita Gordienko, Yuriy Kochura, Yuri Gordienko, Alexandr Rokovyi, Oleg Alienin, Sergii Stirenko

Here the results of application of several deep learning architectures (PSPNet and ICNet) for semantic image segmentation of traffic stereo-pair images are presented.

Self-Driving Cars Semantic Segmentation

Deep Learning for Fatigue Estimation on the Basis of Multimodal Human-Machine Interactions

no code implementations30 Dec 2017 Yuri Gordienko, Sergii Stirenko, Yuriy Kochura, Oleg Alienin, Michail Novotarskiy, Nikita Gordienko

The new method is proposed to monitor the level of current physical load and accumulated fatigue by several objective and subjective characteristics.

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