Deep Learning para Detecção de Componentes em Alimentadores de Subestações
Bruno Alberto Soares Oliveira, Abilio Pereira de Faria Neto, Roberto Márcio Arruda Fernandino, Diego de Proença Costa, Frederico G Guimaraes

DOI: 10.14209/SBRT.2020.1570640122
Evento: XXXVIII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2020)
With each passing year, the consumption of electric energy in Brazil and in the world increases, making it necessary to adopt measures such as the construction of new plants and the installation of electrical structures. The monitoring of construction management in companies is still done in person and manually, resulting in expenses that could be avoided. The objective of this study is to enable a proof of concept by applying the Yolo object detector to a set of images that correspond to devices that make up bays in substations. The results show that it is possible to contribute to the monitoring of construction sites with research in this field.