Development of a web system to annotate and verify images for use in a deep learning system to monitor pest control
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Palavras-chave

Deep learning
Image processing
Smart monitoring

Como Citar

PETRACHINI, Alexandre; LOTUFO, Roberto; KUNO, Yugo. Development of a web system to annotate and verify images for use in a deep learning system to monitor pest control. Revista dos Trabalhos de Iniciação Científica da UNICAMP, Campinas, SP, n. 27, p. 1–1, 2019. DOI: 10.20396/revpibic2720192360. Disponível em: https://econtents.bc.unicamp.br/eventos/index.php/pibic/article/view/2360. Acesso em: 29 mar. 2024.

Resumo

The goal of this research project is to develop a web system that will be used by an entomologist to annotate images taken of adhesive traps for insects. Those images of traps will be photographed on cell phones and sent to a remote server for further annotation on the individual position of each insect contained in the trap. Those annotations will be fundamental to train a deep learning system that automatically recognizes the pests in the images and, by using those annotations, count them appropriately. The system is part of a bigger project to monitor pest control, and it was developed in partnership by the companies Colly Química and NeuralMind.

https://doi.org/10.20396/revpibic2720192360
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Referências

PESQUISA IDENTIFICA RESISTÊNCIA DA MOSCA-DOS-ESTÁBULOS A INSETICIDA. EMBRAPA. Available in: <https://www.embrapa.br/busca-de-noticias/-/noticia/20420229/pesquisa-identifica-resistencia-da-mosca-dos-estabulos-a-inseticida>. Accessed in: 10 jun. 2018.

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