An Exploratory Approach to Deriving Nutrition Information of Restaurant Food from Crowdsourced Food Images: Case of Hartford.

Chen, Xiang; Johnson, Evelyn; Kulkarni, Aditya; Ding, Caiwen; Ranelli, Natalie; Chen, Yanyan; Xu, Ran

Chen, Xiang; Johnson, Evelyn; Kulkarni, Aditya; Ding, Caiwen; Ranelli, Natalie; Chen, Yanyan; Xu, Ran.

Afiliación

Chen X; Department of Geography, University of Connecticut, Storrs, CT 06269, USA.
Johnson E; Department of Allied Health Sciences, University of Connecticut, Storrs, CT 06269, USA.
Kulkarni A; Department of Computer Science & Engineering, University of Connecticut, Storrs, CT 06269, USA.
Ding C; Department of Computer Science & Engineering, University of Connecticut, Storrs, CT 06269, USA.
Ranelli N; Department of Allied Health Sciences, University of Connecticut, Storrs, CT 06269, USA.
Chen Y; Department of Allied Health Sciences, University of Connecticut, Storrs, CT 06269, USA.
Xu R; Department of Allied Health Sciences, University of Connecticut, Storrs, CT 06269, USA.

Nutrients ; 13(11)2021 Nov 18.

Article en En | MEDLINE | ID: mdl-34836387

Asunto(s)

Colaboración de las Masas; Aprendizaje Profundo; Análisis de los Alimentos/métodos; Nutrientes/análisis; Fotograbar; Tramo Censal; Connecticut; Etiquetado de Alimentos; Humanos; Valor Nutritivo; Restaurantes

Palabras clave

FAFH; GIS; Hartford; crowdsourcing; deep learning; food environment; food image; image recognition; nutrition assessment; restaurant

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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Fotograbar / Nutrientes / Colaboración de las Masas / Análisis de los Alimentos / Aprendizaje Profundo Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Nutrients Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

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