Investigation of a Sparse Autoencoder-Based Feature Transfer Learning Framework for Hydrogen Monitoring Using Microfluidic Olfaction Detectors.

Mirzaei, Hamed; Ramezankhani, Milad; Earl, Emily; Tasnim, Nishat; Milani, Abbas S; Hoorfar, Mina

Mirzaei, Hamed; Ramezankhani, Milad; Earl, Emily; Tasnim, Nishat; Milani, Abbas S; Hoorfar, Mina.

Afiliación

Mirzaei H; School of Engineering, University of British Columbia Okanagan Campus, Kelowna, BC V1V 1V7, Canada.
Ramezankhani M; School of Engineering, University of British Columbia Okanagan Campus, Kelowna, BC V1V 1V7, Canada.
Earl E; Department of Mechanical Engineering, University of Victoria, Victoria, BC V8P 5C2, Canada.
Tasnim N; Department of Mechanical Engineering, University of Victoria, Victoria, BC V8P 5C2, Canada.
Milani AS; School of Engineering, University of British Columbia Okanagan Campus, Kelowna, BC V1V 1V7, Canada.
Hoorfar M; Department of Mechanical Engineering, University of Victoria, Victoria, BC V8P 5C2, Canada.

Sensors (Basel) ; 22(20)2022 Oct 11.

Article en En | MEDLINE | ID: mdl-36298047

Asunto(s)

Hidrógeno; Microfluídica; Hidrógeno/análisis; Gas Natural; Olfato; Gases/análisis; Óxidos; Carbono; Aprendizaje Automático

Palabras clave

HENG; hydrogen detection; microfluidic gas sensor; sparse autoencoder; transfer learning

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Microfluídica / Hidrógeno Tipo de estudio: Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article País de afiliación: Canadá

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