JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
Tobacco Sales Bill Recognition Based on Multi-Branch Residual Network |
| 영문제목(English Title) |
Tobacco Sales Bill Recognition Based on Multi-Branch Residual Network |
| 저자(Author) |
Yuxiang Shan
Cheng Wang
Qin Ren
Xiuhui Wang
|
| 원문수록처(Citation) |
VOL 18 NO. 03 PP. 0311 ~ 0318 (2022. 06) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Tobacco sales enterprises often need to summarize and verify the daily sales bills, which may consume substantial manpower, and manual verification is prone to occasional errors. The use of artificial intelligence technology to realize the automatic identification and verification of such bills offers important practical significance. This study presents a novel multi-branch residual network for tobacco sales bills to improve the efficiency and accuracy of tobacco sales. First, geometric correction and edge alignment were performed on the input sales bill image. Second, the multi-branch residual network recognition model is established and trained using the preprocessed data. The comparative experimental results demonstrated that the correct recognition rate of the proposed method reached 98.84% on the China Tobacco Bill Image dataset, which is superior to that of most existing recognition methods. |
| 키워드(Keyword) |
Artificial Intelligence
Image Recognition
Residual Network
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| 파일첨부 |
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