International Journal of Electrical, Electronics and Data Communication (IJEEDC)
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Volume-7,Issue-12  ( Dec, 2019 )
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Statistics report
Feb. 2020
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 84
Paper Published : 1397
No. of Authors : 3784
  Journal Paper

Paper Title
Study on Handwritten Recognition Neural Network Model using Fine Tuning and SELU Activation Function

Abstract
In this paper, we describe how to implement handwritten recognition system using neural network model. Fine tuning was applied to the neural network model VGG16 to improve performance. As a result, this method achieved an accuracy of more than 80%. We also compared the performance of the model using selu as the activation function of VGG16 top model without input data normalization and the model using relu as the activation function of VGG16 top model after input data normalization. As a result, the loss converges more rapidly when the activation function selu is used, and it is confirmed that the activation function selu is effective for improving the learning speed. Keywords - Fine tuning, Handwritten recognition, SELU, VGG16


Author - Jongho Im, Sangjo Kim, Mikyung Kim, Euiyoung Cha

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| Published on 2018-04-09
   
   
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