Your browser doesn't support javascript.
loading
Deep Learning-Based Quantitative Assessment of Melamine and Cyanuric Acid in Pet Food Using Fourier Transform Infrared Spectroscopy.
Joshi, Rahul; Gg, Lakshmi Priya; Faqeerzada, Mohammad Akbar; Bhattacharya, Tanima; Kim, Moon Sung; Baek, Insuck; Cho, Byoung-Kwan.
Afiliación
  • Joshi R; Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, Daejeon 34134, Republic of Korea.
  • Gg LP; Department of Multimedia, VIT School of Design (V-SIGN), Vellore Institute of Technology (VIT), Vellore 632014, India.
  • Faqeerzada MA; Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, Daejeon 34134, Republic of Korea.
  • Bhattacharya T; Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, Daejeon 34134, Republic of Korea.
  • Kim MS; Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture, Powder Mill Road, BARC-East, Bldg 303, Beltsville, MD 20705, USA.
  • Baek I; Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture, Powder Mill Road, BARC-East, Bldg 303, Beltsville, MD 20705, USA.
  • Cho BK; Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, Daejeon 34134, Republic of Korea.
Sensors (Basel) ; 23(11)2023 May 24.
Article en En | MEDLINE | ID: mdl-37299748
Asunto(s)
Palabras clave
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article