Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Aleksey Lukashin"'
Publikováno v:
Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 622, Iss 25, Pp 234-240 (2019)
The article discusses a method for comparing the shape of three-dimensional objects, which was developed at the Peter the Great St. Petersburg Polytechnic University. The main method is the consecutive double conversion of the original three- dimensi
Externí odkaz:
https://doaj.org/article/005469f07a54424496f744de5bbc3bd5
Publikováno v:
Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 622, Iss 25, Pp 220-227 (2019)
Most of the used computer aided diagnostic (CAD) systems based on applying the deep learning algorithms are similar from the point of view of data processing stages. The main typical stages are the training data acquisition, pre- processing, segmenta
Externí odkaz:
https://doaj.org/article/c32fc2c304184d11b5ccd563a5b84c7d
Publikováno v:
Proceedings of International Scientific Conference on Telecommunications, Computing and Control ISBN: 9789813366312
In this paper, we highlight the distinctive features and critical areas of analytical tool application for the employee performance analytics of user activity. We describe problems of applying data analytics methods and technologies to ensure employe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1e4bf48438d569ba0155709abdc6d9fa
https://doi.org/10.1007/978-981-33-6632-9_28
https://doi.org/10.1007/978-981-33-6632-9_28
Publikováno v:
2020 XXIII International Conference on Soft Computing and Measurements (SCM).
An adaptive weighted deep survival forest model for survival analysis is proposed. It can be regarded as an extension of the adaptive weighted deep forest. First, it is based on the deep forest being an ensemble-based model including a set of the ran
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f318d53c25246d38f8994584dbc51f5e
https://doi.org/10.1109/scm50615.2020.9198755
https://doi.org/10.1109/scm50615.2020.9198755