Fruit and Vegetable Information System Using Embedded Convolutional Neural Networks

This article presents the development of a mobile application that exploits a Convolutional Neural Network (CNN) to recognize a set of fruits and vegetables by processing snapshots taken by the built-in camera of the device. We built an acquisition system to gather pictures of different kinds of fru...

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Bibliographic Details
Published in2019 IEEE Latin American Conference on Computational Intelligence (LA-CCI) pp. 1 - 5
Main Authors Bocanegra, Ricardo Munoz, Sotelo, Jesus Alfonso Lopez, Satizabal, Hector, Uribe, Andres Perez
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2019
Subjects
Cameras
CNN
Computational modeling
Feature extraction
Fruits
Image color analysis
Information System
Mobile Application
Mobile handsets
Training
Transfer Learning
Vegetables
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Summary:This article presents the development of a mobile application that exploits a Convolutional Neural Network (CNN) to recognize a set of fruits and vegetables by processing snapshots taken by the built-in camera of the device. We built an acquisition system to gather pictures of different kinds of fruits and vegetables to train a neural network model. Instead of defining a new topology and training it from scratch, we took advantage of transfer learning and fine-tuned several MobileNet models to classify our images in their corresponding classes on a smartphone. Once the fruit or vegetable is identified, our mobile application provides valuable nutritional information about it.
DOI:10.1109/LA-CCI47412.2019.9037057