Comparative and performance analysis of food volume estimation and monitoring food intake for hospitalised patients using deep convolutional neural network and feed forward neural network.

Autor:	Parthiban, T., Anbazhagan, K.
Předmět:	CONVOLUTIONAL neural networks FOOD chemistry FOOD consumption COMPARATIVE studies
Zdroj:	AIP Conference Proceedings; 2023, Vol. 2822 Issue 1, p1-7, 7p
Abstrakt:	To Implement a comparative performance analysis of food volume estimation and monitoring food intake for hospitalized patient using deep convolutional neural networks and feed forward neural network. Deep convolutional neural networks and feed forward neural networks with sample size for both groups (N=10) for finding accuracy. Food estimation based on the obtained result the accuracy rate of Deep convolutional neural networks is 95.65 which is higher than the accuracy rate of feed forward neural networks (90.50). Statistical significance difference observed between two groups is P = 0.00 (P < 0.05) 2-tailed based on independent sample T test. In this paper, it is observed that Deep Convolutional Neural Network has more accuracy than Feed forward neural network. [ABSTRACT FROM AUTHOR]
Databáze:	Complementary Index
Externí odkaz:	Zobrazit plný text záznamu