Image-Based Food Calorie Estimation Using Recipe Information-Reference-Cited by-同舟云学术

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Image-Based Food Calorie Estimation Using Recipe Information

Published:2018-05-01 Issue:5 Volume:E101.D Page:1333-1341
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

EGE Takumi¹,YANAI Keiji¹

Affiliation:

1. Department of Informatics, The University of Electro-Communications

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://www.jstage.jst.go.jp/article/transinf/E101.D/5/E101.D_2017MVP0027/_pdf

Reference22 articles.

1. [1] A. Myers, N. Johnston, V. Rathod, A. Korattikara, A. Gorban, N. Silberman, S. Guadarrama, G. Papandreou, J. Huang, and P.K. Murphy, “Im2calories: towards an automated mobile vision food diary,” Proc. IEEE International Conference on Computer Vision, pp.1233-1241, 2015. 10.1109/iccv.2015.146

2. [2] K. Okamoto and K. Yanai, “An automatic calorie estimation system of food images on a smartphone,” Proc. ACM MM Workshop on Multimedia Assisted Dietary Management, pp.63-70, 2016. 10.1145/2986035.2986040

3. [3] R. Tanno, K. Okamoto, and K. Yanai, “Deepfoodcam: A dcnn-based real-time mobile food recognition system,” Proc. ACM MM Workshop on Multimedia Assisted Dietary Management, p.89, 2016. 10.1145/2986035.2986044

4. [4] J. Dehais, M. Anthimopoulos, and S. Mougiakakou, “Gocarb: A smartphone application for automatic assessment of carbohydrate intake,” Proc. ACM MM Workshop on Multimedia Assisted Dietary Management, p.91 2016. 10.1145/2986035.2986046

5. [5] F. Kong and J. Tan, “Dietcam: Automatic dietary assessment with mobile camera phones,” Proc. Pervasive and Mobile Computin, pp.147-163, 2012. 10.1016/j.pmcj.2011.07.003

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