Fundamentals of deep neural networks - application based in convolutional networks
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Keywords

Deep neural networks
Machine learning
Computational inteligence

How to Cite

GONÇALVES, Rafael; ATTUX, Romis. Fundamentals of deep neural networks - application based in convolutional networks. Revista dos Trabalhos de Iniciação Científica da UNICAMP, Campinas, SP, n. 27, p. 1–1, 2019. DOI: 10.20396/revpibic2720193040. Disponível em: https://econtents.sbu.unicamp.br/eventos/index.php/pibic/article/view/3040. Acesso em: 13 oct. 2026.

Abstract

Deep neural networks are becoming the state-of-the-art in the field of machine learning, especially because of their notable performance in a variety of current problems. Among these algorithms we can cite convolutional neural networks as one of the most powerful models for image classification problems. This research aimed to perform a theoretical study on deep neural networks, as well as to implement a convolutional neural network applied to the problem of handwritten digits classification.

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References

Goodfellow, I.; Bengio, Y.; Courville, A. Deep Learning. 2016.
LeCun, Y. The MNIST Database of Handwritten Digits. Available at: http://yann.lecun.com/ exdb/mnist/ . Last acessed in: 07/07/2019.
Gonçalves, R. MNIST nn. Avaiable at: https://github.com/RafaelGoncalves8/ mnist_nn/. Last acessed in: 07/07/2019.
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