A Comprehensive Introduction to Neural Convolutional Networks: A Case Study for Character Recognition
Convolutional neural networks have been attracted great attention in the realm of complex tasks, mainly in image recognition. They were specifically designed to process images as inputs, as they act in local receptive fields, performing a convolution process. However, understanding the work principl...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Faculdade Salesiana Maria Auxiliadora
2018-12-01
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| Series: | Sistemas de Informação |
| Subjects: | |
| Online Access: | http://www.fsma.edu.br/si/edicao21/Download_FSMA_SI_2018_1_Principal_8_en.html |
| Summary: | Convolutional neural networks have been attracted great attention in the realm of complex tasks, mainly in image recognition. They were specifically designed to process images as inputs, as they act in local receptive fields, performing a convolution process. However, understanding the work principle of this network may not be an easy task, especially for beginners in the area of computational intelligence. Therefore, the objective of this work is to present in a didactic and intuitive way the convolutional neural networks. A case study involving alphabet character recognition is presented in order to ilustrate the feasibility of the approach. |
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| ISSN: | 1983-5604 1983-5604 |