Classify Ecuadorian Receipes with Convolutional Neural Networks

被引：0

作者：

Soria, Luis ^{[1
]}

Jimenez Cadena, Gabriela Alejandra ^{[2
]}

Eduardo Martinez, Carlos ^{[3
]}

Castillo Salazar, David R. ^{[4
]}

机构：

[1] Univ Int SEK, Fac Arquitectura & Ingenierias, Quito, Ecuador

[2] Pontificia Univ Catolica Ecuador, Fac Arquitectura Diserio & Artes, Quito, Ecuador

[3] Univ Reg Autonoma Andes, Sistemas, Km 5 1-2 Via Banos, Ambato, Ecuador

[4] Univ Indoamer, Ambato, Ecuador

来源：

INFORMATION TECHNOLOGY AND SYSTEMS, ICITS 2020 | 2020年 / 1137卷

关键词：

Food dishes; Photos; Parallel; FOOD;

D O I：

10.1007/978-3-030-40690-5_22

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This work is a proposal to resolve the problem of identification plates of food through photographs. It involves using a large set of pictures which are processed by convolutional neural networks and parallel processing TensorFlow. The results show a 90% greater accuracy in training and between 63% and 80% in the test. The reason is that Ecuadorian dishes are very similar in the images of some recipes.

引用

页码：223 / 229

页数：7

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