Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Marcos Rogozinski"'
Autor:
Marcos Rogozinski, Carlos Roberto Hall Barbosa, Raul Queiroz Feitosa, Bryan R.C. Oliveira, Elisabeth Costa Monteiro, Daniel Ramos Louzada
Publikováno v:
Measurement: Sensors, Vol 18, Iss , Pp 100133- (2021)
This paper presents an algorithm based on Convolutional Neural Networks (CNN) to find the depth and angles of inclination and rotation of a foreign object inside the human body based on images of the magnetic field generated by it. The key challenge
Externí odkaz:
https://doaj.org/article/cb33273ae2c54a41b05d52ad8be6f2d9
Publikováno v:
Measurement: Sensors, Vol 18, Iss , Pp 100275- (2021)
This paper presents a tracking system to find the position and yaw rotation of a handheld device based on the imaging of an adhesive marker attached to a person's body. Our goal is to provide accurate data that can be combined with data from a giant
Externí odkaz:
https://doaj.org/article/55f580ecd2f04d72a9497c93ad857838
Autor:
MARCOS ROGOZINSKI
[pt] Corpos estranhos ferromagnéticos inseridos acidentalmente em pacientes geralmente precisam de remoção cirúrgica. Os métodos convencionalmente empregados para localizar corpos estranhos são frequentemente ineficazes devido à baixa precisã
Publikováno v:
International Journal of Remote Sensing. 43:6056-6077
The increasing food demand is regarded as the main threat to nature today. In this scenario, Remote Rensing is an essential technology to assess and monitor the extent and productivity of cultivate...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::260882f174f4f70bf6f8a592e60d28fa
https://doi.org/10.1080/01431161.2021.1976876
https://doi.org/10.1080/01431161.2021.1976876
Publikováno v:
IEEE Latin America Transactions. 19:446-455
Many countries are experiencing a transformation from the traditional generation power system into a smart grid which incorporates communication and data processing technologies. New services become possible and are important to improve the system op
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ffc3429b3618e61c80ae90383c3ddab
https://doi.org/10.1109/tla.2021.9447694
https://doi.org/10.1109/tla.2021.9447694
Autor:
MARCOS ROGOZINSKI
Publikováno v:
Repositório Institucional da PUC-RIO (Projeto Maxwell)
Pontifícia Universidade Católica do Rio de Janeiro (PUC-RIO)
instacron:PUC_RIO
Pontifícia Universidade Católica do Rio de Janeiro (PUC-RIO)
instacron:PUC_RIO
PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTITUIÇÕES COMUNITÁRIAS DE ENSINO PARTICULARES Corpos estranhos ferromagnéticos inse
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3056::a9978fbe86bde33a09f131a8c5ba668e
https://www.maxwell.vrac.puc-rio.br/colecao.php?strSecao=resultado&nrSeq=57112@2
https://www.maxwell.vrac.puc-rio.br/colecao.php?strSecao=resultado&nrSeq=57112@2
Publikováno v:
IGARSS
This paper introduces a novel hybrid N-to-N bidirectional ConvLSTM for multi-temporal crop recognition in areas characterized by highly complex crop dynamics as in tropical regions. The proposed method seeks to explore both spatial and temporal conte
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::69da9e0d5c20c000a18796086a00da8e
https://doi.org/10.1109/igarss47720.2021.9554782
https://doi.org/10.1109/igarss47720.2021.9554782
Autor:
Raul Queiroz Feitosa, Elisabeth Costa Monteiro, Carlos Roberto Hall Barbosa, Daniel Ramos Louzada, Marcos Rogozinski, Bryan R. C. de Oliveira
Publikováno v:
Measurement: Sensors, Vol 18, Iss, Pp 100133-(2021)
This paper presents an algorithm based on Convolutional Neural Networks (CNN) to find the depth and angles of inclination and rotation of a foreign object inside the human body based on images of the magnetic field generated by it. The key challenge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::526231be8f0298a9a22f4016bbfed65c
https://doi.org/10.1016/j.measen.2021.100133
https://doi.org/10.1016/j.measen.2021.100133