Application of Deep Learning in Automated Meal Recognition

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

Abstract

Deep learning is a widely used data analysis tool and has its proven value in solving problems and challenges in data science. In the nutrition domain, automated recognition of meals is an essential task within the food quality control and diet management. Adequate food supply and precise distribution of nutrients are extremely important. The availability of deep learning to facilitate these tasks would improve a critical step of the meal service process. Therefore, the aim of this research is to study deep learning applications as automated meal recognition for patients at the Canberra Hospital, specifically using convolutional neural networks (CNN). The application of applying deep learning to food quality control are important in reducing human mistakes that may result to providing wrong foods to patients in the current food service at Canberra Hospital.
Original languageEnglish
Title of host publication2020 IEEE Symposium Series on Computational Intelligence (SSCI)
EditorsHussain Abbass, Carlos A. Coello Coello, Hemant Kumar Singh
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages58-63
Number of pages6
ISBN (Electronic)9781728125473
ISBN (Print)9781728125480
DOIs
Publication statusPublished - 5 Jan 2021
Event2020 IEEE Symposium Series on Computational Intelligence (SSCI) - Canberra, Canberra, Australia
Duration: 1 Dec 20204 Dec 2020
http://www.ieeessci2020.org/

Conference

Conference2020 IEEE Symposium Series on Computational Intelligence (SSCI)
Abbreviated titleSSCI 2020
CountryAustralia
CityCanberra
Period1/12/204/12/20
Internet address

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