形成卷积神经网络训练/测试样本的实践方面

Y. Tomka, M. Talakh, V. Dvorzhak, O. Ushenko
{"title":"形成卷积神经网络训练/测试样本的实践方面","authors":"Y. Tomka, M. Talakh, V. Dvorzhak, O. Ushenko","doi":"10.31649/1681-7893-2022-43-1-24-35","DOIUrl":null,"url":null,"abstract":"The most common approaches to assessing the quality of training neural networks in the context of the problem of \"small training sets\" are analyzed. A review of the code implementation of the most universal approaches and ways of extending training/testing samples is carried out. The logic of the work of STN-module is analyzed. It can be inserted into existing convolutional architectures, giving neural networks the ability to actively spatially transform feature maps, conditional on the feature map itself, without any extra training supervision or modification to the optimization process.","PeriodicalId":142101,"journal":{"name":"Optoelectronic information-power technologies","volume":"161 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Practical Aspects of Forming Training/Test Samples for Convolutional Neural Networks\",\"authors\":\"Y. Tomka, M. Talakh, V. Dvorzhak, O. Ushenko\",\"doi\":\"10.31649/1681-7893-2022-43-1-24-35\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The most common approaches to assessing the quality of training neural networks in the context of the problem of \\\"small training sets\\\" are analyzed. A review of the code implementation of the most universal approaches and ways of extending training/testing samples is carried out. The logic of the work of STN-module is analyzed. It can be inserted into existing convolutional architectures, giving neural networks the ability to actively spatially transform feature maps, conditional on the feature map itself, without any extra training supervision or modification to the optimization process.\",\"PeriodicalId\":142101,\"journal\":{\"name\":\"Optoelectronic information-power technologies\",\"volume\":\"161 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Optoelectronic information-power technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31649/1681-7893-2022-43-1-24-35\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optoelectronic information-power technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31649/1681-7893-2022-43-1-24-35","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

分析了在“小训练集”问题背景下评估训练神经网络质量的最常见方法。对最通用的方法和扩展训练/测试样本的方法的代码实现进行审查。分析了stn模块的工作逻辑。它可以插入到现有的卷积架构中,使神经网络能够主动地对特征映射进行空间变换,以特征映射本身为条件,无需任何额外的训练监督或对优化过程进行修改。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Practical Aspects of Forming Training/Test Samples for Convolutional Neural Networks
The most common approaches to assessing the quality of training neural networks in the context of the problem of "small training sets" are analyzed. A review of the code implementation of the most universal approaches and ways of extending training/testing samples is carried out. The logic of the work of STN-module is analyzed. It can be inserted into existing convolutional architectures, giving neural networks the ability to actively spatially transform feature maps, conditional on the feature map itself, without any extra training supervision or modification to the optimization process.
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
期刊最新文献
Detection of armed people in a video stream using convolutional neural networks Approximation of the distribution function of the reflectiveness of the surface by the third-degree polynom Intelligent system for identifying the user's trust rating Review of research towards the myoelectric method of controlling bionic prosthesis The use of laser therapy in herpesvirus injuries of the peripheral nervous system
×
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