Menu Text Recognition of Few-shot Learning  

作　　者：Xiaoyu Tian Zhenzhen Xin Zihao Liu Suolan Chen Fuhua Wang Hongyuan 

机构地区：[1]School of Computer Science and Artificial Intelligencea,Changzhou,213164,China [2]Changzhou University,Changzhou,Jiangsu,213164,China [3]West Liberty University,208 University Drive,West Liberty,26074,USA

出　　处：《Journal of New Media》2022年第3期137-143,共7页新媒体杂志（英文）

基　　金：supported by the Advanced Training Project of the Professional Leaders in Jiangsu Higher Vocational Colleges (2020GRFX006).

摘　　要：Recent advances in OCR show that end-to-end(E2E)training pipelines including detection and identification can achieve the best results.However,many existing methods usually focus on case insensitive English characters.In this paper,we apply an E2E approach,the multiplex multilingual mask TextSpotter,which performs script recognition at the word level and uses different recognition headers to process different scripts while maintaining uniform loss,thus optimizing script recognition and multiple recognition headers simultaneously.Experiments show that this method is superior to the single-head model with similar number of parameters in endto-end identification tasks.

关 键 词：Text recognition script identification few-shot learning multiple languages 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]