The estimation system of food texture considering sound and load using neural networks

Autor:	Naoki Wada, Ryuji Ito, Yuma Goto, Naruse Murakami, Shigeru Kato, Rina Kondo
Rok vydání:	2017
Předmět:	Estimation geography geography.geographical_feature_category Artificial neural network Computer science Load modeling 020206 networking & telecommunications 04 agricultural and veterinary sciences 02 engineering and technology computer.software_genre 040501 horticulture Food texture 0202 electrical engineering electronic engineering information engineering Quantitative Biology::Populations and Evolution Data mining 0405 other agricultural sciences computer ComputingMilieux_MISCELLANEOUS Sound (geography)
Zdroj:	2017 International Conference on Biometrics and Kansei Engineering (ICBAKE).
Popis:	This paper aims at construction of a system which assumes food textures. The system consists of equipment for obtaining the load and the sound signals while the probe is stabbing the food, and the neural network model infers the degree of the food texture. In the experiment, the validity of our proposed system is discussed.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::533809ac3bb79ef4e79758e1f45ec13c https://doi.org/10.1109/icbake.2017.8090622 Zobrazit plný text záznamu