This paper is in the following e-collection/theme issue:

Wearable Devices and Sensors (968) New Methods (1012) Imaging Informatics (221) Machine Learning (1662) Instruments and Questionnaires for Nutrition and Food Intake (181) Evaluation and Research Methodology for mHealth (218) mHealth for Wellness, Behavior Change and Prevention (3050)

Published on in Vol 9, No 1 (2021): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21926, first published .
Deep Learning–Based Multimodal Data Fusion: Case Study in Food Intake Episodes Detection Using Wearable Sensors

Deep Learning–Based Multimodal Data Fusion: Case Study in Food Intake Episodes Detection Using Wearable Sensors

Deep Learning–Based Multimodal Data Fusion: Case Study in Food Intake Episodes Detection Using Wearable Sensors

Authors of this article:

Nooshin Bahador1 Author Orcid Image ;   Denzil Ferreira1 Author Orcid Image ;   Satu Tamminen1 Author Orcid Image ;   Jukka Kortelainen1 Author Orcid Image
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New in JMIR mhealth: Deep Learning–Based Multimodal Data Fusion: Case Study in Food Intake Episodes Detection Using… https://t.co/bWfxh27Y4h

2:14 PM · Jan 28, 2021

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Denzil Ferreira ???? Denzil Ferreira ???? @denzilferreira

Using multimodal data fusion to monitor food intake @ubicomp_oulu with Nooshin Bahador, Jukka Kortelainen, Satu Tam… https://t.co/gAeSufNvMy

5:50 PM · Jan 28, 2021

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RT @denzilferreira: Using multimodal data fusion to monitor food intake @ubicomp_oulu with Nooshin Bahador, Jukka Kortelainen, Satu Tammine…

11:46 AM · Jan 29, 2021

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Deep Learning & Data Fusion: detección de episodios de ingesta de alimentos. Sensores para los gestos de la mano a… https://t.co/lqnabZ5wHh

8:05 AM · Feb 24, 2021

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RT @blendarsys: Deep Learning & Data Fusion: detección de episodios de ingesta de alimentos. Sensores para los gestos de la mano a la boca…

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