Author of the publication

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Prediction of unregistered power consumption lawsuits and its correlated factors based on customer data using extreme gradient boosting model.

F. de Oliveira, A. Silva, E. Alves, M. de Oliveira, L. Pinheiro, P. Cutrim, J. Diniz, G. da Silva, D. Quintanilha, O. da Silva Neto, V. Fernandes, G. Junior, and A. Cavalcante. SMC, page 2059-2064. IEEE, (2019)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Kerstin da Silva

Rodrigo Corrêa da Silva

Adriano João Da Silva

Carolina Ferraz da Silva

Antonio Da Silva Mello

Other publications of authors with the same name

Superpixel-based deep convolutional neural networks and active contour model for automatic prostate segmentation on 3D MRI scans.G. da Silva, P. Diniz, J. Ferreira, J. França, A. Silva, A. de Paiva, and E. de Cavalcanti. Medical Biol. Eng. Comput., 58 (9): 1947-1964 (2020)Automatic Prostate Segmentation on 3D MRI Scans Using Convolutional Neural Networks with Residual Connections and Superpixels.G. da Silva, J. França, P. Diniz, A. Silva, A. de Paiva, and E. de Cavalcanti. IWSSIP, page 51-56. IEEE, (2020)An ergonomic evaluation method using a mobile depth sensor and pose estimation.P. de Freitas, P. Mendes, A. Busson, Á. Guedes, G. da Silva, A. de Paiva, and S. Colcher. WebMedia, page 445-452. ACM, (2019)Deployment of a Machine Learning System for Predicting Lawsuits Against Power Companies: Lessons Learned from an Agile Testing Experience for Improving Software Quality.L. Rivero, J. Diniz, G. da Silva, G. Borralho, G. Junior, A. de Paiva, E. Alves, and M. de Oliveira. SBQS, page 30. ACM, (2020)Convolutional neural network-based PSO for lung nodule false positive reduction on CT images.G. da Silva, T. Valente, A. Silva, A. de Paiva, and M. Gattass. Comput. Methods Programs Biomed., (2018)Heart segmentation in planning CT using 2.5D U-Net++ with attention gate.J. Diniz, D. Júnior, L. da Cruz, G. da Silva, J. Ferreira, D. Quintanilha, A. Silva, A. de Paiva, and M. Gattass. Comput. methods Biomech. Biomed. Eng. Imaging Vis., 11 (3): 317-325 (May 2023)Prediction of unregistered power consumption lawsuits and its correlated factors based on customer data using extreme gradient boosting model.F. de Oliveira, A. Silva, E. Alves, M. de Oliveira, L. Pinheiro, P. Cutrim, J. Diniz, G. da Silva, D. Quintanilha, O. da Silva Neto and 3 other author(s). SMC, page 2059-2064. IEEE, (2019)Taxonomic Indexes for Automatic Prostate Segmentation on 3D MRI Scans Using Superpixels and Probabilistic Atlas.J. França, G. da Silva, P. dos Santos, G. Junior, A. Silva, and E. de Cavalcanti. IWSSIP, page 122-127. IEEE, (2020)

BibSonomy

Disambiguation of "da Silva, Giovanni Lucca França"

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Prediction of unregistered power consumption lawsuits and its correlated factors based on customer data using extreme gradient boosting model.

Please choose a person to relate this publication to

Kerstin da Silva

Rodrigo Corrêa da Silva

Adriano João Da Silva

Carolina Ferraz da Silva

Antonio Da Silva Mello

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "da Silva, Giovanni Lucca França"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Prediction of unregistered power consumption lawsuits and its correlated factors based on customer data using extreme gradient boosting model.

Please choose a person to relate this publication to

Kerstin da Silva

Rodrigo Corrêa da Silva

Adriano João Da Silva

Carolina Ferraz da Silva

Antonio Da Silva Mello

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Prediction of unregistered power consumption lawsuits and its correlated factors based on customer data using extreme gradient boosting model.