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基于微服务架构的众包图像数据集标注系统
引用本文:袁晓晨,张卫山,高绍姝,时斌,赵永俊,王冶,安云云. 基于微服务架构的众包图像数据集标注系统[J]. 计算机系统应用, 2021, 30(5): 83-91. DOI: 10.15888/j.cnki.csa.007900
作者姓名:袁晓晨  张卫山  高绍姝  时斌  赵永俊  王冶  安云云
作者单位:中国石油大学(华东) 计算机科学与技术学院, 青岛 266580;青岛海尔空调电子有限公司 电控模块开发部, 青岛 266101;解放军9144部队, 青岛 266102;国网山东省电力公司 青岛市黄岛区供电公司, 青岛 266500
基金项目:国家自然科学基金(62072469); 国家重点科研计划(2018YFE0116700); 山东省自然科学基金(ZR2019MF049); 中央高校基础研究基金(2015020031); 西海岸人工智能技术创新中心建设专项(2019-1-5, 2019-1-6); 上海可信工业控制平台开放项目(TICPSH202003015-ZC)
摘    要:深度学习在图像识别领域凸显出了优势,而在深度学习图像识别模型训练的准备阶段,制备图像数据集需要人工将图片上的信息进行标注.这一准备过程往往需要耗费大量人力成本与时间成本.为了提升数据制备阶段的工作效率,从而加速深度学习模型的生成与迭代,提出了一种基于微服务架构的多人协作众包式图像数据集标注系统.通过将繁重的标注任务划分...

关 键 词:微服务  Spring Cloud  持续集成  持续部署  图像标注
收稿时间:2020-09-10
修稿时间:2020-10-09

Image Dataset Annotation System in Crowdsourcing Based on Microservice Architecture
YUAN Xiao-Chen,ZHANG Wei-Shan,GAO Shao-Shu,SHI Bin,ZHAO Yong-Jun,WANG Ye,AN Yun-Yun. Image Dataset Annotation System in Crowdsourcing Based on Microservice Architecture[J]. Computer Systems& Applications, 2021, 30(5): 83-91. DOI: 10.15888/j.cnki.csa.007900
Authors:YUAN Xiao-Chen  ZHANG Wei-Shan  GAO Shao-Shu  SHI Bin  ZHAO Yong-Jun  WANG Ye  AN Yun-Yun
Affiliation:College of Computer Science and Technology, China University of Petroleum, Qingdao 266580, China;Electronic Control Module Development Department, Haier Air Conditioning Electronic Ltd. (Qingdao), Qingdao 266101, China;No. 9144 Troops of PLA, Qingdao 266102, China; Qingdao Huangdao District Power Supply Company, State Grid Shandong Electric Power Company, Qingdao 266500, China
Abstract:Deep learning has shown visible advantages in the artificial intelligence-based image classification. It usually costs plenty of time on manual information annotation for preparing image datasets. Then this study proposes an online collaborative system for image dataset annotation based on microservice architecture to improve the efficiency of annotating datasets and thus to accelerate the generation and iteration of deep learning models and applications. More users can join for image annotation after the heavy annotation task is divided into smaller ones. Besides, the system performance has been improved by introducing an object storage system and microservice architecture, and the integration efficiency of the system in the development progress has been enhanced by continuous integration and deployment.
Keywords:microservice  Spring Cloud  continuous integration  continuous deployment  image annotation
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