FoodDeep
A digital tool for estimating the amount of food using deep learning - [2022 - 2024] Key Words: Deep Learning, Food Data Analysis, Image Segmentation, Food Volume Estimation
Name of the project: A digital tool for estimating the amount of food using deep learning
Name principal investigator (PI): Petia Radeva
Funding entity: Ministry of Science and Innovation
Duration: 01/12/2022 - 30/11/2024
Why Food recognition and Food Volume Estimation? Today we live in conditions of increasing work stress and hectic lifestyle that inherently have adverse effects on our health. Fortunately, there is a rise in awareness of the importance of maintaining health via good eating habits and exercises.
A digital tool for estimating the amount of food using deep learning. The aim of DeepFoodVol is to optimise from the point of view of time running, extensively test and generate a prototype of our Deep learning algorithms to be integrated into an innovative dietary assessment application tool ready to provide precise feedback on user’s food intake and nutritional status.
Members involved
Petia I. Radeva
Research lines
Deep learning for food computing
Latest news
Inaugural Event of ELLIS Unit Barcelona
The Ellis Unit Barcelona was successfully inaugurated on 12th of July, 2024 Friday at the Institut d’Estudis Catalans (IEC), Barcelona.
Read moreTFG Thesis of Oscar Blasquez and Adrian Galan
We are proud to announce that our TFG students achieved the highest grade of 10 on their TFG thesis.
Read moreInvited Talk of Prof. Petia Radeva at Metafood Workshop CVPR’24
Prof. Petia Radeva was invited to give a talk to Metafood Workshop- CVPR 2024.
Read moreBhalaji’s PhD with “Cum Laude”
We are proud to announce that our team member Bhalaji Nagarajan has earned his doctorate and is now Dr. Bhalaji Nagarajan.
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