DOIONLINE 
DOIONLINE Publish In |
International Journal of Electrical, Electronics and Data Communication (IJEEDC)-IJEEDC |
 Journal Home Volume Issue |
||||||||
Issue |
Volume-6,Issue-2 ( Feb, 2018 ) | |||||||||
Paper Title |
Study on Handwritten Recognition Neural Network Model using Fine Tuning and SELU Activation Function | |||||||||
Author Name |
Jongho Im, Sangjo Kim, Mikyung Kim, Euiyoung Cha | |||||||||
Affilition |
Dept of Electricity and Electronic Computer Engineering, Pusan National University, South Korea | |||||||||
Pages |
23-24 | |||||||||
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 | |||||||||
| View Paper | ||||||||||
