Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Rokovyi, Oleksandr"'
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, and everyday life even. This work reports about application of some ma
Externí odkaz:
http://arxiv.org/abs/1912.09848
Open Source Dataset and Machine Learning Techniques for Automatic Recognition of Historical Graffiti
Autor:
Gordienko, Nikita, Gang, Peng, Gordienko, Yuri, Zeng, Wei, Alienin, Oleg, Rokovyi, Oleksandr, Stirenko, Sergii
Publikováno v:
In: Cheng L., Leung A., Ozawa S. (eds) Neural Information Processing. ICONIP 2018. Lecture Notes in Computer Science, vol. 11305, pp. 414-424. Springer, Cham
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 (Ukraine). A new image dataset of these carved Glagolitic and Cyrillic letter
Externí odkaz:
http://arxiv.org/abs/1808.10862
Autor:
Stirenko, Sergii, Peng, Gang, Zeng, Wei, Gordienko, Yuri, Alienin, Oleg, Rokovyi, Oleksandr, Gordienko, Nikita
Publikováno v:
In: Vaidya J., Li J. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2018. Lecture Notes in Computer Science, vol 11334, 483-497. Springer, Cham
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 analysis of accumulated and moving window data subsets with construction of
Externí odkaz:
http://arxiv.org/abs/1808.04760
Autor:
Stirenko, Sergii, Kochura, Yuriy, Alienin, Oleg, Rokovyi, Oleksandr, Gang, Peng, Zeng, Wei, Gordienko, Yuri
Publikováno v:
2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO), Kiev, 2018, pp. 422-428
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 of deep learning are presented. They demonstrate the efficiency of lun
Externí odkaz:
http://arxiv.org/abs/1803.01199
Autor:
Gordienko, Yuri, Kochura, Yuriy, Taran, Vlad, Gordienko, Nikita, Rokovyi, Oleksandr, Alienin, Oleg, Stirenko, Sergii
Publikováno v:
In Advances in Computers 2021 122:303-341
