Classify ecuadorian receipes with convolutional neural networks

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. © Springer Nature Switzerland AG 2020.