Classify Ecuadorian Receipes with Convolutional Neural Networks
| Autor: | David R. Castillo Salazar, Luis Soria, Carlos Eduardo Martinez, Gabriela Alejandra Jimenez Cadena |
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| Rok vydání: | 2020 |
| Předmět: |
Identification (information)
Parallel processing (DSP implementation) Computer science business.industry 0202 electrical engineering electronic engineering information engineering 020206 networking & telecommunications 020201 artificial intelligence & image processing Pattern recognition 02 engineering and technology Artificial intelligence business Convolutional neural network |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783030406899 ICITS |
| DOI: | 10.1007/978-3-030-40690-5_22 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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