Výsledky vyhledávání - "Carolina L. S. Cipriano"

A Chatbot Solution for Self-Reading Energy Consumption via Chatting Applications

Autor: Carlos Vinicios Martins Rocha, Eduardo Camacho Fernandes, Anderson Matheus Passos Paiva, Italo Francyles Santos da Silva, Arthur Azevedo Lima, Eliana Márcia Garros Monteiro, Pedro Henrique Carvalho Vieira, Carolina L. S. Cipriano, Hugo Daniel Castro Silva Nogueira, Aristófanes Corrêa Silva, Simara Vieira da Rocha

Publikováno v: Journal of Control, Automation and Electrical Systems

To mitigate financial loss and follow the recommended sanitary measures due to the COVID-19 pandemic, self-reading, a method in which a consumer reads and reports his own energy consumption, has been presented as an efficient alternative for power co

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::14ef3b38e927c007ee4b1690b39ba3f4
https://doi.org/10.1007/s40313-021-00818-6

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Segmentation and quantification of COVID-19 infections in CT using pulmonary vessels extraction and deep learning

Publikováno v: Multimedia Tools and Applications

At the end of 2019, the World Health Organization (WHO) reported pneumonia that started in Wuhan, China, as a global emergency problem. Researchers quickly advanced in research to try to understand this COVID-19 and sough solutions for the front-line

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aca0657d9df0da23135c682eee6f62c0
http://europepmc.org/articles/PMC8224997

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Temporal Convolutional Network applied for Forecasting Individual Monthly Electric Energy Consumption

Autor: Márcia Izabel Alves da Silva, Geraldo Braz Junior, Anselmo Cardoso de Paiva, Eduardo Camacho Fernandes, Carolina L. S. Cipriano, Aristófanes Corrêa Silva, Victor Henrique Bezerra de Lemos, Alan Carlos de Moura Lima, João Dallyson Sousa de Almeida, Stelmo M. B. Neto

Publikováno v: SMC

The task of predicting energy consumption is a problem of great interest in electric power companies. A minimal error prediction is essential for identifying inconsistencies in the monthly consumption reading process. This paper presents a methodolog

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1833a466a49c8a8c37f580ee7326f3f8
https://doi.org/10.1109/smc42975.2020.9282960

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Forecasting of individual electricity consumption using Optimized Gradient Boosting Regression with Modified Particle Swarm Optimization

Autor: Darlan B. P. Quintanilha, João Otávio Bandeira Diniz, Petterson Sousa Diniz, João Dallyson Sousa de Almeida, Carolina L. S. Cipriano, Eliana Márcia Garros Monteiro, Aristófanes Corrêa Silva, Anselmo Cardoso de Paiva, Márcia Izabel Alves da Silva, Alexandre C. P. Pessoa, Geraldo Braz, Victor Henrique Bezerra de Lemos, Luis Fernando Marin Sepulveda, Alexandre Cristian Araújo, Stelmo Magalhães Barros Netto, Italo Francyles Santos da Silva, Eduardo Camacho Fernandes

Publikováno v: Engineering Applications of Artificial Intelligence. 105:104440

The task of forecasting consumers’ energy consumption is currently a trend in energy supply companies. An accurate prediction of energy consumption is a powerful tool to check for inconsistencies between what is recorded and the actual amount consu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3b4a5858449b69b9906d35565ea1093c
https://doi.org/10.1016/j.engappai.2021.104440

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Classification of brain lesions on magnetic resonance imaging using superpixel, PSO and convolutional neural network

Autor: Anselmo Cardoso de Paiva, Jonnison Lima Ferreira, Carolina L. S. Cipriano, Aristófanes Corrêa Silva, Giovanni Lucca França da Silva

Publikováno v: Anais do XV Workshop de Visão Computacional (WVC 2019).

One of the most severe and common brain tumors is gliomas. Manual classiﬁcation of injuries of this type is a laborious task in the clinical routine. Therefore, this work proposes an automatic method to classify lesions in the brain in 3D MR images

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8423e952c1efb7d8f9e6e4cca7f42be9
https://doi.org/10.5753/wvc.2019.7640

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Segmentação automática de lesões no cérebro em imagens de ressonância magnética usando superpixel, PSO e a rede geradora adversária com classificador auxiliar

Autor: Anselmo Cardoso de Paiva, Giovanni Faria Silva, Aristófanes Corrêa Silva, Carolina L. S. Cipriano, Jonnison Lima Ferreira

Publikováno v: Anais do Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS 2019).

Gliomas são um dos tumores cerebrais mais severos. No entanto, a segmentação manual é uma tarefa difı́cil e demorada. Portanto, esse trabalho propõe um método automático para a segmentação de sub-regiões de lesões no cérebro em imagens

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::245d711634071afd73251d1b83991659
https://doi.org/10.5753/sbcas.2019.6254

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