%0 Conference Proceedings
%T Uncertainty Modeling and Deep Learning Applied to Food Image Analysis
%A Eduardo Aguilar
%A Bhalaji Nagarajan
%A Rupali Khatun
%A Marc Bolaños
%A Petia Radeva
%B 13th International Joint Conference on Biomedical Engineering Systems and Technologies
%D 2020
%F Eduardo Aguilar2020
%O MILAB
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=3526), last updated on Mon, 08 Feb 2021 12:30:56 +0100
%X Recently, computer vision approaches specially assisted by deep learning techniques have shown unexpected advancements that practically solve problems that never have been imagined to be automatized like face recognition or automated driving. However, food image recognition has received a little effort in the Computer Vision community. In this project, we review the field of food image analysis and focus on how to combine with two challenging research lines: deep learning and uncertainty modeling. After discussing our methodology to advance in this direction, we comment potential research, social and economic impact of the research on food image analysis.
%U http://dx.doi.org/10.5220/0009429400090016