Food image analysis: The big data problem you can eat!
dc.contributor.author | Wang, Y. | |
dc.contributor.author | Fang, S. | |
dc.contributor.author | Liu, C. | |
dc.contributor.author | Zhu, F. | |
dc.contributor.author | Kerr, D. | |
dc.contributor.author | Boushey, Carol | |
dc.contributor.author | Delp, E. | |
dc.date.accessioned | 2017-04-28T13:58:38Z | |
dc.date.available | 2017-04-28T13:58:38Z | |
dc.date.created | 2017-04-28T09:06:10Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Wang, Y. and Fang, S. and Liu, C. and Zhu, F. and Kerr, D. and Boushey, C. and Delp, E. 2017. Food image analysis: The big data problem you can eat!, pp. 1263-1267. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/52407 | |
dc.identifier.doi | 10.1109/ACSSC.2016.7869576 | |
dc.description.abstract |
© 2016 IEEE.Six of the ten leading causes of death in the United States can be directly linked to diet. Measuring accurate dietary intake, the process of determining what someone eats is considered to be an open research problem in the nutrition and health fields. We are developing image-based tools in order to automatically obtain accurate estimates of what foods a user consumes. We have developed a novel food record application using the embedded camera in a mobile device. This paper describes the current status of food image analysis and overviews problems that still need to be addressed. | |
dc.title | Food image analysis: The big data problem you can eat! | |
dc.type | Conference Paper | |
dcterms.source.startPage | 1263 | |
dcterms.source.endPage | 1267 | |
dcterms.source.title | Conference Record - Asilomar Conference on Signals, Systems and Computers | |
dcterms.source.series | Conference Record - Asilomar Conference on Signals, Systems and Computers | |
dcterms.source.isbn | 9781538639542 | |
curtin.department | School of Public Health | |
curtin.accessStatus | Fulltext not available |
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