Multimedia foodlog: Diverse applications from self-monitoring to social contributions, ITE Transactions on Media Technology and Applications, 2013. ,
Comparative Study of the Routine Daily Usability of FoodLog, Journal of Diabetes Science and Technology, vol.6, issue.2, 2014. ,
DOI : 10.1177/1932296814522745
Food Balance Estimation by Using Personal Dietary Tendencies in a Multimedia Food Log, IEEE Transactions on Multimedia, 2013. ,
DOI : 10.1109/TMM.2013.2271474
An Overview of the Technology Assisted Dietary Assessment Project at Purdue University, 2010 IEEE International Symposium on Multimedia, 2010. ,
DOI : 10.1109/ISM.2010.50
Food-101 ??? Mining Discriminative Components with Random Forests, ECCV, 2014. ,
DOI : 10.1007/978-3-319-10599-4_29
URL : https://lirias.kuleuven.be/bitstream/123456789/507027/1/3931_postprint.pdf
PFID: Pittsburgh fast-food image dataset, 2009 16th IEEE International Conference on Image Processing (ICIP), 2009. ,
DOI : 10.1109/ICIP.2009.5413511
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.158.54
A Benchmark Dataset to Study the Representation of Food Images, ACVR, 2014. ,
DOI : 10.1007/978-3-319-16199-0_41
A database for fine grained activity detection of cooking activities, 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012. ,
DOI : 10.1109/CVPR.2012.6247801
FoodCam: A Real-Time Mobile Food Recognition System Employing Fisher Vector, MMM, 2014. ,
DOI : 10.1007/978-3-319-04117-9_38
Food image recognition with deep convolutional features, Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct Publication, UbiComp '14 Adjunct, 2014. ,
DOI : 10.1145/2638728.2641339
Automatic Expansion of a Food Image Dataset Leveraging Existing Categories with Domain Adaptation, Proc. of ECCV Workshop on TASK-CV, 2014. ,
DOI : 10.1007/978-3-319-16199-0_1
Harvesting image databases from the web, 2011. ,
LIBLINEAR: A library for large linear classification, 2008. ,
Pooling in image representation: The visual codeword point of view, Computer Vision and Image Understanding, vol.117, issue.5, 2013. ,
DOI : 10.1016/j.cviu.2012.09.007
URL : https://hal.archives-ouvertes.fr/hal-01172709
Very deep convolutional networks for large-scale image recognition, 2014. ,
Distributed representations of words and phrases and their compositionality, NIPS, 2013. ,
Distributed Representations of Sentences and Documents, ICML, 2014. ,
SALSAS: Sub-linear active learning strategy with approximate k-NN search, Pattern Recognition, vol.44, issue.10-11, pp.2343-2357, 2011. ,
DOI : 10.1016/j.patcog.2010.12.009
URL : https://hal.archives-ouvertes.fr/hal-00773102
Active Learning Methods for Interactive Image Retrieval, IEEE Transactions on Image Processing, vol.17, issue.7, pp.1200-1211, 2008. ,
DOI : 10.1109/TIP.2008.924286
URL : https://hal.archives-ouvertes.fr/hal-00520292
Image Retrieval Over Networks: Active Learning Using Ant Algorithm, IEEE Transactions on Multimedia, vol.10, issue.7, pp.1356-1365, 2008. ,
DOI : 10.1109/TMM.2008.2004913
URL : https://hal.archives-ouvertes.fr/hal-00656363