MC-OCR挑战:越南收据的移动捕获图像文档识别

Xuan-Son Vu, Quang-Anh Bui, Nhu-Van Nguyen, Thi-Tuyet-Hai Nguyen, Thanh Vu
{"title":"MC-OCR挑战:越南收据的移动捕获图像文档识别","authors":"Xuan-Son Vu, Quang-Anh Bui, Nhu-Van Nguyen, Thi-Tuyet-Hai Nguyen, Thanh Vu","doi":"10.1109/RIVF51545.2021.9642077","DOIUrl":null,"url":null,"abstract":"The paper describes the organisation of the \"Mobile Captured Receipt Recognition Challenge\" (MC-OCR) task at the RIVF conference 2021 1 on recognizing the fine-grained information in Vietnamese receipts captured using mobile devices. The task is organized as a multi-tasking model on a dataset containing 2,436 Vietnamese receipts. The participants were challenged to build a model that is capable of (1) predicting receipt’s quality based on readable information, and (2) recognizing textual information of four required information (i.e., \"SELLER\", \"SELLER ADDRESS\", \"TIMESTAMP\", and \"TOTAL COST\") in the receipts. MC-OCR challenge happened in one month and top winners of each task will present their solutions at RIVF 2021. Participants were competing on CodaLab.Org from 05th December 2020 to 23rd January 2021. All participants with valid submitted results were encouraged to submit their papers. Within one month, the challenge has attracted 105 participants and recorded about 1,285 submission entries.","PeriodicalId":6860,"journal":{"name":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"1 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"MC-OCR Challenge: Mobile-Captured Image Document Recognition for Vietnamese Receipts\",\"authors\":\"Xuan-Son Vu, Quang-Anh Bui, Nhu-Van Nguyen, Thi-Tuyet-Hai Nguyen, Thanh Vu\",\"doi\":\"10.1109/RIVF51545.2021.9642077\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper describes the organisation of the \\\"Mobile Captured Receipt Recognition Challenge\\\" (MC-OCR) task at the RIVF conference 2021 1 on recognizing the fine-grained information in Vietnamese receipts captured using mobile devices. The task is organized as a multi-tasking model on a dataset containing 2,436 Vietnamese receipts. The participants were challenged to build a model that is capable of (1) predicting receipt’s quality based on readable information, and (2) recognizing textual information of four required information (i.e., \\\"SELLER\\\", \\\"SELLER ADDRESS\\\", \\\"TIMESTAMP\\\", and \\\"TOTAL COST\\\") in the receipts. MC-OCR challenge happened in one month and top winners of each task will present their solutions at RIVF 2021. Participants were competing on CodaLab.Org from 05th December 2020 to 23rd January 2021. All participants with valid submitted results were encouraged to submit their papers. Within one month, the challenge has attracted 105 participants and recorded about 1,285 submission entries.\",\"PeriodicalId\":6860,\"journal\":{\"name\":\"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)\",\"volume\":\"1 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RIVF51545.2021.9642077\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RIVF51545.2021.9642077","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14

摘要

该论文描述了在2021年RIVF会议1上组织的“移动捕获收据识别挑战”(MC-OCR)任务,该任务旨在识别使用移动设备捕获的越南收据中的细粒度信息。该任务在包含2,436个越南收据的数据集上组织为多任务模型。参与者被要求建立一个模型,该模型能够(1)基于可读信息预测收据的质量,(2)识别收据中四个必需信息(即“卖方”、“卖方地址”、“时间戳”和“总成本”)的文本信息。MC-OCR挑战在一个月内进行,每个任务的优胜者将在RIVF 2021上展示他们的解决方案。参与者在CodaLab上进行竞争。2020年12月5日至2021年1月23日。我们鼓励所有提交了有效结果的参与者提交论文。在一个月内,这项挑战吸引了105名参与者,并记录了约1,285份参赛作品。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MC-OCR Challenge: Mobile-Captured Image Document Recognition for Vietnamese Receipts
The paper describes the organisation of the "Mobile Captured Receipt Recognition Challenge" (MC-OCR) task at the RIVF conference 2021 1 on recognizing the fine-grained information in Vietnamese receipts captured using mobile devices. The task is organized as a multi-tasking model on a dataset containing 2,436 Vietnamese receipts. The participants were challenged to build a model that is capable of (1) predicting receipt’s quality based on readable information, and (2) recognizing textual information of four required information (i.e., "SELLER", "SELLER ADDRESS", "TIMESTAMP", and "TOTAL COST") in the receipts. MC-OCR challenge happened in one month and top winners of each task will present their solutions at RIVF 2021. Participants were competing on CodaLab.Org from 05th December 2020 to 23rd January 2021. All participants with valid submitted results were encouraged to submit their papers. Within one month, the challenge has attracted 105 participants and recorded about 1,285 submission entries.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信