most citedComparative Analysis of Open Source Frameworks for Machine Learning with Use Case in Single-Threaded and Multi-Threaded Modes

28 citations · 53 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2017★ 1 cited

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…

cs.SD2017

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…

cs.DC2017★ 20 cited

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…

cs.HC2017★ 4 cited

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…

cs.LG2017★ 28 cited

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…