KaIDA:深度学习图像标注辅助模块化工具。

IF 1.5 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Journal of Integrative Bioinformatics Pub Date : 2022-08-26 eCollection Date: 2022-12-01 DOI:10.1515/jib-2022-0018
Marcel P Schilling, Svenja Schmelzer, Lukas Klinger, Markus Reischl
{"title":"KaIDA:深度学习图像标注辅助模块化工具。","authors":"Marcel P Schilling, Svenja Schmelzer, Lukas Klinger, Markus Reischl","doi":"10.1515/jib-2022-0018","DOIUrl":null,"url":null,"abstract":"<p><p>Deep learning models achieve high-quality results in image processing. However, to robustly optimize parameters of deep neural networks, large annotated datasets are needed. Image annotation is often performed manually by experts without a comprehensive tool for assistance which is time- consuming, burdensome, and not intuitive. Using the here presented modular Karlsruhe Image Data Annotation (KaIDA) tool, for the first time assisted annotation in various image processing tasks is possible to support users during this process. It aims to simplify annotation, increase user efficiency, enhance annotation quality, and provide additional useful annotation-related functionalities. KaIDA is available open-source at https://git.scc.kit.edu/sc1357/kaida.</p>","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9800041/pdf/","citationCount":"5","resultStr":"{\"title\":\"KaIDA: a modular tool for assisting image annotation in deep learning.\",\"authors\":\"Marcel P Schilling, Svenja Schmelzer, Lukas Klinger, Markus Reischl\",\"doi\":\"10.1515/jib-2022-0018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Deep learning models achieve high-quality results in image processing. However, to robustly optimize parameters of deep neural networks, large annotated datasets are needed. Image annotation is often performed manually by experts without a comprehensive tool for assistance which is time- consuming, burdensome, and not intuitive. Using the here presented modular Karlsruhe Image Data Annotation (KaIDA) tool, for the first time assisted annotation in various image processing tasks is possible to support users during this process. It aims to simplify annotation, increase user efficiency, enhance annotation quality, and provide additional useful annotation-related functionalities. KaIDA is available open-source at https://git.scc.kit.edu/sc1357/kaida.</p>\",\"PeriodicalId\":53625,\"journal\":{\"name\":\"Journal of Integrative Bioinformatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2022-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9800041/pdf/\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Integrative Bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1515/jib-2022-0018\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/12/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"MATHEMATICAL & COMPUTATIONAL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Integrative Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/jib-2022-0018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/12/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 5

摘要

深度学习模型在图像处理中取得了高质量的结果。然而,要稳健地优化深度神经网络的参数,就需要大型注释数据集。图像标注通常由专家手工完成,没有全面的工具辅助,耗时长、负担重且不直观。利用这里介绍的模块化卡尔斯鲁厄图像数据注释(Karlsruhe Image Data Annotation,KaIDA)工具,首次可以在各种图像处理任务中进行辅助注释,在此过程中为用户提供支持。该工具旨在简化注释、提高用户效率、提升注释质量,并提供更多有用的注释相关功能。KaIDA开源于 https://git.scc.kit.edu/sc1357/kaida。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

KaIDA: a modular tool for assisting image annotation in deep learning.

KaIDA: a modular tool for assisting image annotation in deep learning.

KaIDA: a modular tool for assisting image annotation in deep learning.

KaIDA: a modular tool for assisting image annotation in deep learning.

Deep learning models achieve high-quality results in image processing. However, to robustly optimize parameters of deep neural networks, large annotated datasets are needed. Image annotation is often performed manually by experts without a comprehensive tool for assistance which is time- consuming, burdensome, and not intuitive. Using the here presented modular Karlsruhe Image Data Annotation (KaIDA) tool, for the first time assisted annotation in various image processing tasks is possible to support users during this process. It aims to simplify annotation, increase user efficiency, enhance annotation quality, and provide additional useful annotation-related functionalities. KaIDA is available open-source at https://git.scc.kit.edu/sc1357/kaida.

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
Journal of Integrative Bioinformatics
Journal of Integrative Bioinformatics Medicine-Medicine (all)
CiteScore
3.10
自引率
5.30%
发文量
27
审稿时长
12 weeks
×
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