Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Arpad Kerestely"'
Publikováno v:
IEEE Access, Vol 11, Pp 123924-123937 (2023)
Bug reports are generated in large numbers during the software development processes in the software industry. The manual processing of these issues is usually time consuming and prone to errors, consequently delaying the entire software development
Externí odkaz:
https://doaj.org/article/d7e23ae9fc684faaa0a4d16c28a32091
Autor:
Arpad Kerestely
Publikováno v:
SERIES III - MATEMATICS, INFORMATICS, PHYSICS. 13:705-714
Efficient High Performance Computing for Machine Learning has become a necessity in the past few years. Data is growing exponentially in domains like healthcare, government, economics and with the development of IoT, smartphones and gadgets. This big
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::771a4f19f9688e2875249afa25bfdbf0
https://doi.org/10.31926/but.mif.2020.13.62.2.26
https://doi.org/10.31926/but.mif.2020.13.62.2.26
Publikováno v:
Knowledge Science, Engineering and Management ISBN: 9783030821524
KSEM
KSEM
With the removal of the hydatidiform mole it has been shown that the human chorionic gonadotropin (hCG) hormone levels drop exponentially in women diagnosed with Gestational Trophoblastic Disease (GTD). This papers aims to introduce a new method at f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d1b2f2b7349eba3a0051ec795363922
https://doi.org/10.1007/978-3-030-82153-1_35
https://doi.org/10.1007/978-3-030-82153-1_35
Publikováno v:
Knowledge Science, Engineering and Management ISBN: 9783030821357
KSEM
KSEM
The design and implementation of proactive fault diagnosis systems concerning the bearings during their manufacturing process requires the selection of robust representation learning techniques, which belong to the broader scope of the machine learni
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::01fb80dbdf41be1e495cc0834393aab0
https://doi.org/10.1007/978-3-030-82136-4_25
https://doi.org/10.1007/978-3-030-82136-4_25