FWA: Visual Food Waste Analysis for Sustainable Kitchens
Description
A novel approach for a fully automated food waste management solution for commercial kitchens is investigated. Food waste is automatically detected using a new camera device, preprocessed in real-time and classified using machine learning algorithms.
Key Data
Projectlead
Co-Projectlead
Project team
Mohammadreza Amirian, Philipp Andermatt, Dr. Ricardo Chavarriaga, Rico Ganahl, Philipp Huber, Dr. Amin Mazloumian, Dominic Mösch, Pascal Sager, kein Titel Yvan Putra Satyawan, Prof. Dr. Frank-Peter Schilling, Raphael Zingg
Project partners
Kitro SA
Project status
completed, 07/2019 - 09/2021
Funding partner
Innovationsprojekt / Projekt Nr. 36777.1 IP-ICT
Project budget
435'610 CHF
Publications
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Smart food waste management : embedded machine learning vs cloud based solutions
2021 Zingg, Raphael; Andermatt, Philipp; Mazloumian, Amin; Rosenthal, Matthias
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A survey of un-, weakly-, and semi-supervised learning methods for noisy, missing and partial labels in industrial vision applications
2021 Simmler, Niclas; Sager, Pascal; Andermatt, Philipp; Chavarriaga, Ricardo; Schilling, Frank-Peter; Rosenthal, Matthias; Stadelmann, Thilo
Technikumstrasse 20/22
8400 Winterthur