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Patent Searching and Data


Title:
METHOD, APPARATUS AND SYSTEM FOR TRAINING TEXT RECOGNITION MODEL FRAMEWORK
Document Type and Number:
WIPO Patent Application WO/2023/005253
Kind Code:
A1
Abstract:
The present disclosure relates to the technical field of artificial intelligence, and in particular to the technical fields of computer vision and deep learning, and can be applied in smart city and smart finance scenarios. Provided are a method, apparatus and system for training a text recognition model framework. The method comprises: performing feature processing on a sample image on the basis of a preset text detection model, so as to obtain at least two types of feature information related to text information in the sample image; performing fusion processing on the at least two types of feature information of the sample image on the basis of a preset feature fusion model, so as to obtain a fused feature of the sample image; and inputting the fused feature into the feature fusion model, and respectively adjusting parameters of the text detection model and the feature fusion model on the basis of the fused feature, so as to obtain a text recognition model framework. The text detection model and the feature fusion model in the text recognition model framework have a relatively high relevance, so as to realize the integrity and comprehensiveness of a training process, thereby improving the accuracy and reliability of the text recognition model framework.

Inventors:
ZHANG CHENGQUAN (CN)
LV PENGYUAN (CN)
LI YULIN (CN)
YU YUECHEN (CN)
YAO KUN (CN)
HAN JUNYU (CN)
LIU JINGTUO (CN)
DING ERRUI (CN)
WU TIAN (CN)
WANG HAIFENG (CN)
Application Number:
PCT/CN2022/085149
Publication Date:
February 02, 2023
Filing Date:
April 02, 2022
Export Citation:
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Assignee:
BEIJING BAIDU NETCOM SCI & TECH CO LTD (CN)
International Classes:
G06K9/62; G06K9/00
Foreign References:
CN113591864A2021-11-02
CN109271967A2019-01-25
CN111507355A2020-08-07
CN111738251A2020-10-02
CN110163110A2019-08-23
Attorney, Agent or Firm:
LEADER PATENT & TRADEMARK FIRM (CN)
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