Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Francisco Caio M. Rodrigues"'
Publikováno v:
VISIGRAPP (3: IVAPP)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dfdf0ec7b4464866dc756e50b97f395d
https://doi.org/10.5220/0010288501230132
https://doi.org/10.5220/0010288501230132
Autor:
Javam C. Machado, Lucas G. M. Leite, Lucas P. Queiroz, Iago C. Chaves, Felipe T. Brito, Francisco Caio M. Rodrigues, João P. P. Gomes
Publikováno v:
New Generation Computing. 36:5-19
Detecting faults in Hard Disk Drives (HDD) can lead to significant benefits to HDD manufacturers, users and storage system providers. As a consequence, several works have focused on the development of fault detection algorithms for HDDs. Recently, pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::54bebfbca2b1fef9ba43c00d29b81d6c
https://doi.org/10.1007/s00354-017-0016-0
https://doi.org/10.1007/s00354-017-0016-0
Autor:
Iago C. Chaves, Lucas P. Queiroz, Francisco Caio M. Rodrigues, Manoel Rui P. Paula, Felipe T. Brito, João P. P. Gomes, Javam C. Machado, M.R. Salvador
Publikováno v:
IEEE Transactions on Industrial Informatics. 13:542-550
Hard Disk Drives (HDD) failure prediction is a challenging topic that has attracted much attention in recent years. Predicting failures in HDD may avoid losing data thus improving data reliability. Previous works on failure prediction are based on pa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::08d53bb286b414afaa6cabb0d5cef052
https://doi.org/10.1109/tii.2016.2619180
https://doi.org/10.1109/tii.2016.2619180
Publikováno v:
Information, Vol 10, Iss 9, p 280 (2019)
Information
Volume 10
Issue 9
AHF-Information, 10(9):280. MDPI AG
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Information
Volume 10
Issue 9
AHF-Information, 10(9):280. MDPI AG
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Visualizing decision boundaries of machine learning classifiers can help in classifier design, testing and fine-tuning. Decision maps are visualization techniques that overcome the key sparsity-related limitation of scatterplots for this task. To inc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::323651e6a905e1a3e82df2bbb57d7007
https://www.mdpi.com/2078-2489/10/9/280
https://www.mdpi.com/2078-2489/10/9/280
Publikováno v:
Proceedings-31st Conference on Graphics, Patterns and Images, SIBGRAPI 2018, 353-360
STARTPAGE=353;ENDPAGE=360;TITLE=Proceedings-31st Conference on Graphics, Patterns and Images, SIBGRAPI 2018
SIBGRAPI
STARTPAGE=353;ENDPAGE=360;TITLE=Proceedings-31st Conference on Graphics, Patterns and Images, SIBGRAPI 2018
SIBGRAPI
Understanding how a classifier partitions a high-dimensional input space and assigns labels to the parts is an important task in machine learning. Current methods for this task mainly use color-coded sample scatterplots, which do not explicitly show
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ae3749b14874393416989e8fdca4c6d
http://www.scopus.com/inward/record.url?scp=85062244171&partnerID=8YFLogxK
http://www.scopus.com/inward/record.url?scp=85062244171&partnerID=8YFLogxK
Publikováno v:
VISIGRAPP (3: IVAPP)
Visualizing decision boundaries of modern machine learning classifiers can notably help in classifier design, testing, and fine-tuning. Dense maps are a very recent method that overcomes the key sparsity-related limitation of scatterplots for this ta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::20663b8fa828175f23d55f9de7db72d4
https://doi.org/10.5220/0007260800280038
https://doi.org/10.5220/0007260800280038
Autor:
Nina S. T. Hirata, Leandro Ticlia De La Cruz, Roberto Hirata, Rubens M. Lopes, Antonio A. Abello, Francisco Caio M. Rodrigues
Publikováno v:
VISIGRAPP (5: VISAPP)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1a37861b2ebe06c7b3f02dbdeba1477
https://doi.org/10.5220/0006626703590366
https://doi.org/10.5220/0006626703590366
Autor:
Javam C. Machado, Francisco Caio M. Rodrigues, Lucas P. Queiroz, Iago C. Brito, Felipe T. Brito, João P. P. Gomes
Publikováno v:
BRACIS
Being able to detect faults in Hard Disk Drives (HDD) can lead to significant benefits to computer manufacturers, users and storage system providers. As a consequence, several works have focused on the development of fault detection algorithms for HD
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1270bf2575e27b53ea445a431d837ee5
https://doi.org/10.1109/bracis.2016.036
https://doi.org/10.1109/bracis.2016.036
Publikováno v:
BRACIS
Graphics cards are complex electronic systems designed for high performance applications. Due to its processing power, graphics cards may operate at high temperatures, leading its components to a significant degradation level. This fact is even more
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b070daa77b322cb9f693fb383334136d
https://doi.org/10.1109/bracis.2015.38
https://doi.org/10.1109/bracis.2015.38
Autor:
Queiroz, Lucas P.1 lucas.queiroz@lsbd.ufc.br, Gomes, Joao Paulo P.1 joao.pordeus@lsbd.ufc.br, Rodrigues, Francisco Caio M.1 caio.rodrigues@lsbd.ufc.br, Brito, Felipe T.1 felipe.timbo@lsbd.ufc.br, Chaves, Iago C.1 iago.chaves@lsbd.ufc.br, Leite, Lucas G. M.1 lucas.goncalves@lsbd.ufc.br, Machado, Javam C.1 javam.machado@lsbd.ufc.br
Publikováno v:
New Generation Computing. Jan2018, Vol. 36 Issue 1, p5-19. 15p.