Source: Program. Conference titles: Brazil MRS Meeting. Unidade: IFSC
Subjects: APRENDIZADO COMPUTACIONAL, DESCOBERTA DE CONHECIMENTO, SENSOR
ABNT
GALDINO, Nathália Magno et al. Machine learning applied for designing conductive polymers based electrochemical sensors for pesticide. 2022, Anais.. Rio de Janeiro: Sociedade Brasileira de Pesquisa em Materiais - SBPMat, 2022. Disponível em: https://repositorio.usp.br/directbitstream/d9bc3130-ff07-4699-8029-34352397618d/3098363.pdf. Acesso em: 16 set. 2024.APA
Galdino, N. M., Baum, F., Köche, A., Manica, L., Santos, J. F. L., & Oliveira Junior, O. N. de. (2022). Machine learning applied for designing conductive polymers based electrochemical sensors for pesticide. In Program. Rio de Janeiro: Sociedade Brasileira de Pesquisa em Materiais - SBPMat. Recuperado de https://repositorio.usp.br/directbitstream/d9bc3130-ff07-4699-8029-34352397618d/3098363.pdfNLM
Galdino NM, Baum F, Köche A, Manica L, Santos JFL, Oliveira Junior ON de. Machine learning applied for designing conductive polymers based electrochemical sensors for pesticide [Internet]. Program. 2022 ;[citado 2024 set. 16 ] Available from: https://repositorio.usp.br/directbitstream/d9bc3130-ff07-4699-8029-34352397618d/3098363.pdfVancouver
Galdino NM, Baum F, Köche A, Manica L, Santos JFL, Oliveira Junior ON de. Machine learning applied for designing conductive polymers based electrochemical sensors for pesticide [Internet]. Program. 2022 ;[citado 2024 set. 16 ] Available from: https://repositorio.usp.br/directbitstream/d9bc3130-ff07-4699-8029-34352397618d/3098363.pdf