Gaze latent SVM for image classification

X. Wang, N. Thome, M. Cord

IEEE ICIP (2016) p. 2212-2225, vol 12

Max-Min convolutional neural networks for image classification

M. Blot, M. Cord, N. Thome

IEEE ICIP (2016)

LR-CNN For Fine-grained Classification with Varying Resolution

M. Chevalier, N. Thome, M. Cord, J. Fournier, G. Henaff, E. Dutch

IEEE ICIP (2015)

Paper Supplementary

Exemplar Based Metric Learning For Robust Visual Localization

C. Le Barz, N. Thome, M. Cord, M. Sanfourche, S. Herbin

IEEE ICIP (2015)

Paper

MANTRA: Minimum Maximum Latent Structural SVM for Image Classification and Ranking

T. Durand, N. Thome, M. Cord

ICCV (2015)

@article { Bolanos2016,
url = {http://arxiv.org/pdf/1604.07953v1},
eprint = {1604.07953},
arxivid = {1604.07953},
archiveprefix = {arXiv},
month = {Apr},
year = {2016},
booktitle = {arXiv},
title = {Simultaneous Food Localization and Recognition},
author = {Marc Bolaños and Petia Radeva}
}

Recipe Recognition with Large Multimodal Food Dataset

X. Wang, D. Kumar, N. Thome, M. Cord, F. Precioso

Cooking and Eating Activities at IEEE ICME (2015)

Incremental Learning of Latent Structural SVM for Weakly Supervised Image Classification

T. Durand, N. Thome, M. Cord, D. Picard

ICIP (2014)

Semantic Pooling for Image Categorization using Multiple Kernel Learning

T. Durand, D. Picard, N. Thome, M. Cord

ICIP (2014)

Machine Learning Techniques for Multimedia

M. Cord, P. Cunningham (Eds.) (2008)

Case Studies on Organization and Retrieval. Series: Cognitive Technologies

Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it.