Improving Convolutional Neural Network (CNN) architecture (miniVGGNet) with batch normalization and learning rate decay factor for image classification
The image classification is a classical problem of image processing, computer vision, and machine learning. This paper presents an analysis of the performance using Convolutional Neural Network (CNN) for image classifying using deep learning. MiniVGGNet is CNN architecture used in this paper to trai...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
UTHM Publisher
2019
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| Online Access: | http://psasir.upm.edu.my/id/eprint/80197/1/Improving%20Convolutional%20Neural%20Network%20%28CNN%29%20architecture%20%28miniVGGNet%29%20with%20Batch%20Normalization%20and%20Learning%20Rate%20Decay%20Factor%20for%20Image%20Classification.pdf http://psasir.upm.edu.my/id/eprint/80197/ |
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