Research of the properties of receptive field in handwritten Chinese character recognition based on DCNN model

Shan Feng; Peng Guo

doi:10.1117/12.2244561

29 August 2016 Research of the properties of receptive field in handwritten Chinese character recognition based on DCNN model

Shan Feng, Peng Guo

Author Affiliations +

Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 1003311 (2016) https://doi.org/10.1117/12.2244561
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China

Abstract

For problem of influence of different size of receptive fields to DCNN modeling on offline handwritten Chinese character recognition (HCCR), the relationships of the receptive field, the number of parameter, the number of layer, the number of feature map and the size of the area occupied by the basic strokes of Chinese characters have been deeply researched and verified with experiment. With a Softmax classifier of output layer, GPU techniques are applied to accelerate model training and Drop-out method is adopted to prevent over-fitting. The research results of the theory and the experiment are important reference in the light of reasonable or effective selection of receptive field size for DCNN model in HCCR applications. It also provides a method for selecting the size of the receptive field for DCNN in HCCR.

Citation Download Citation

Shan Feng and Peng Guo "Research of the properties of receptive field in handwritten Chinese character recognition based on DCNN model", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 1003311 (29 August 2016); https://doi.org/10.1117/12.2244561

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available