Resumen

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 06-Sep-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.

Palabras clave : Recognition; image; TensorFlow; SVM; Neural Networks.

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