Services on Demand
Journal
Article
Indicators
- Cited by SciELO
- Access statistics
Related links
- Cited by Google
- Similars in SciELO
- Similars in Google
Share
Revista Ingenierías Universidad de Medellín
Print version ISSN 1692-3324On-line version ISSN 2248-4094
Abstract
MUNOZ-CASTANO, Yeny et al. Development of an Application for the Prediction of Kitchen Ingredients and Recipes through TensorFlow and Support-Vector Machines. Rev. ing. univ. Medellín [online]. 2020, vol.19, n.37, pp.195-215. Epub Sep 06, 2021. ISSN 1692-3324. https://doi.org/10.22395/rium.v19n37a10.
This article is derived from a research project in which an application for the prediction of ingredients and recipes by TensorFlow and support-vector machines was developed. A scheme with general architecture was developed, then a neural network was implemented, and then, the support-vector machine was run. After that, they were integrated via an application that allows the user to select ingredients' images for their prediction and the prediction of kitchens recipe in a didactic manner. It was concluded that the system has an average precision value of 75.8% and 71% for 17 ingredients categories and recipes classifier. In addition, sensitivity testing was performed on the application resulting on statistically equivalent results.
Keywords : Recognition; image; TensorFlow; SVM; Neural Networks.