PROCEEDINGS OF THE ITE WINTER ANNUAL CONVENTION
Online ISSN : 2424-2306
Print ISSN : 1343-4357
ISSN-L : 1343-4357
2017 ITE Winter Annual Convention
Session ID : 13B-4
Conference information

Food Image Recognition Based on Deep Feature Considering Time and Distributed Representation
*Qing YUMasashi ANZAWASosuke AMANOToshihiko YAMASAKIKiyoharu AIZAWAMakoto OGAWA
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CONFERENCE PROCEEDINGS FREE ACCESS

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Abstract

In this paper, we proposed a method to improve food image recognition accuracy by extracting better deep features with the latest deep learning network considering mealtime and distributed representation. We also evaluated these features by a personalized classifier.

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© 2017 The Institute of Image Information and Television Engineers
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