Identification of insect infiltration time by tissue slice

Y. Hashiguchi, K. Terada, K. Shinozaki, K. Miyama
{"title":"Identification of insect infiltration time by tissue slice","authors":"Y. Hashiguchi, K. Terada, K. Shinozaki, K. Miyama","doi":"10.1117/12.2588838","DOIUrl":null,"url":null,"abstract":"Since contamination of food products by insects can cause serious damage to manufacturers, it is necessary to determine the timing of contamination as a countermeasure. However, manual surveys are time consuming and expensive. In this paper, we propose a method for automatic identification of insect infiltration routes using image processing.","PeriodicalId":295011,"journal":{"name":"International Conference on Quality Control by Artificial Vision","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Quality Control by Artificial Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2588838","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Since contamination of food products by insects can cause serious damage to manufacturers, it is necessary to determine the timing of contamination as a countermeasure. However, manual surveys are time consuming and expensive. In this paper, we propose a method for automatic identification of insect infiltration routes using image processing.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
组织切片法鉴定昆虫浸润时间
由于食品被昆虫污染会对制造商造成严重损害,因此有必要确定污染时间作为对策。然而,手工调查既耗时又昂贵。本文提出了一种基于图像处理的昆虫渗透路径自动识别方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Single-camera multi-point vision: on the use of robotics for digital image correlation f-AnoGAN for non-destructive testing in industrial anomaly detection Object detection model-based quality inspection using a deep CNN Reducing the latency and size of a deep CNN model for surface defect detection in manufacturing Deep-learning based industrial quality control on low-cost smart cameras
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1