Convolutional Neural Networks and Pattern Recognition: Application to Image Classification
| Main Authors: | Christy Ntambwe Kabamba, Lucie Mpuekela .N, Simon Ntumba .B, Eugene Mbuyi .M |
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| Format: | Article |
| Terbitan: |
, 2019
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/3987070 |
Daftar Isi:
- This research study focuses on pattern recognition using convolutional neural network. Deep neural network has been choosing as the best option for the training process because it produced a high percentage of accuracy. We designed different architectures of convolutional neural network in order to find the one with high accuracy of image classification and optimum bias. We used CIFAR-10 data set that contains 60000 Images to train our model on architectures. The best architecture was able to classify images with 95.55% of accuracy and an error of 0.32% using cross validation method. We note that, the numbers of epoch while running the model and the depth of the architecture are factors that contributed to get this performance.