Offline Handwritten Chinese Character Recognition Based on DBN and CNN Fusion Model
Aiming at the problem that some offline handwritten Chinese characters are similar in shape and it is difficult to extract the feature of characters and the recognition is not accurate, a convolutional neural network and deep belief network fusion model is proposed Firstly, the convolutional neural...
Saved in:
| Main Authors: | LI Lanying, ZHOU Zhigang, CHEN Deyun |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2020-06-01
|
| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1785 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
DBN Fusion Model for Offline Handwritten Chinese Characters Recognition
by: LIU Lu, et al.
Published: (2017-12-01) -
TRANSFER LEARNING BASED OFFLINE YORÙBÁ HANDWRITTEN CHARACTER RECOGNITION SYSTEM
by: OLUWASHINA OYENIRAN, et al.
Published: (2021-10-01) -
Offline Arabic handwritten word recognition: A transfer learning approach
by: Mohamed Awni, et al.
Published: (2022-11-01) -
Handwritten Words Image Character Extraction Adaptive Algorithm Based on the Multi-branch Structure
by: GUO Xiaojing, et al.
Published: (2025-05-01) -
Handwritten Amharic Character Recognition Through Transfer Learning: Integrating CNN Models and Machine Learning Classifiers
by: Natenaile Asmamaw Shiferaw, et al.
Published: (2025-01-01)