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

Crowdsourcing and Mechanical Turks (95) Innovations and Technology for Healthy Eating Education (408) Instruments and Questionnaires for Nutrition and Food Intake (161)

Published on in Vol 21, No 4 (2019): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12047, first published .
Crowdsourcing for Food Purchase Receipt Annotation via Amazon Mechanical Turk: A Feasibility Study

Crowdsourcing for Food Purchase Receipt Annotation via Amazon Mechanical Turk: A Feasibility Study

Crowdsourcing for Food Purchase Receipt Annotation via Amazon Mechanical Turk: A Feasibility Study

Authors of this article:

Wenhua Lu1 Author Orcid Image ;   Alexandra Guttentag2 Author Orcid Image ;   Brian Elbel3, 4 Author Orcid Image ;   Kamila Kiszko3 Author Orcid Image ;   Courtney Abrams3 Author Orcid Image ;   Thomas R Kirchner2 Author Orcid Image
Article Authors Cited by (4) Tweetations (7) Metrics

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  3. Shakeri Hossein Abad Z, Butler G, Thompson W, Lee J. Crowdsourcing for Machine Learning in Public Health Surveillance: Lessons Learned From Amazon Mechanical Turk. Journal of Medical Internet Research 2022;24(1):e28749 View
  4. Li Q, Wang X, Bachani A. Estimating helmet wearing rates via a scalable, low-cost algorithm: a novel integration of deep learning and google street view. BMC Public Health 2024;24(1) View