Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Felipe Ianczyk"'
Autor:
Lucas Prado Osco, Ana Paula Marques Ramos, Mayara Maezano Faita Pinheiro, Érika Akemi Saito Moriya, Nilton Nobuhiro Imai, Nayara Estrabis, Felipe Ianczyk, Fábio Fernando de Araújo, Veraldo Liesenberg, Lúcio André de Castro Jorge, Jonathan Li, Lingfei Ma, Wesley Nunes Gonçalves, José Marcato Junior, José Eduardo Creste
Publikováno v:
Remote Sensing, Vol 12, Iss 6, p 906 (2020)
This paper presents a framework based on machine learning algorithms to predict nutrient content in leaf hyperspectral measurements. This is the first approach to evaluate macro- and micronutrient content with both machine learning and reflectance/fi
Externí odkaz:
https://doaj.org/article/ac169d975121448aae74662bd43ef556
Autor:
Nayara Vasconcelos Estrabis, Mayara Maezano Faita Pinheiro, Wesley Nunes Gonçalves, Érika Akemi Saito Moriya, José Eduardo Creste, Ana Paula Marques Ramos, Felipe Ianczyk, Lúcio André de Castro Jorge, Lingfei Ma, Nilton Nobuhiro Imai, Lucas Prado Osco, Fabio Fernando de Araujo, Jonathan Li, José Marcato Junior, Veraldo Liesenberg
Publikováno v:
Scopus
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
Remote Sensing; Volume 12; Issue 6; Pages: 906
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA-Alice)
Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
Remote Sensing, Vol 12, Iss 6, p 906 (2020)
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
Remote Sensing; Volume 12; Issue 6; Pages: 906
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA-Alice)
Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
Remote Sensing, Vol 12, Iss 6, p 906 (2020)
Made available in DSpace on 2020-12-12T02:00:26Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-03-01 This paper presents a framework based on machine learning algorithms to predict nutrient content in leaf hyperspectral measurements. This is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d77bf5d3fb7c27527134196918fbea27
