Foodness Proposal for Multiple Food Detection by Training of Single Food Images
Author:
Affiliation:
1. The University of Electro-Communications, Tokyo, Chofu, Tokyo, Japan
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2986035.2986043
Reference47 articles.
1. Combining global and local features for food identification in dietary assessment
2. Food-101 – Mining Discriminative Components with Random Forests
3. Automatic Chinese food identification and quantity estimation
4. Automatic Chinese food identification and quantity estimation
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