{"title":"使用卷积神经网络的自动视频可解释性评估","authors":"A. Kalukin","doi":"10.1109/AIPR.2018.8707423","DOIUrl":null,"url":null,"abstract":"A neural network used to automate assessment of video quality, as measured by the Video National Imagery Interpretability Rating Scale (VNIIRS), was able to ascertain the exact VNIIRS rating over 80% of the time.","PeriodicalId":230582,"journal":{"name":"2018 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","volume":"519 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automated Video Interpretability Assessment using Convolutional Neural Networks\",\"authors\":\"A. Kalukin\",\"doi\":\"10.1109/AIPR.2018.8707423\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A neural network used to automate assessment of video quality, as measured by the Video National Imagery Interpretability Rating Scale (VNIIRS), was able to ascertain the exact VNIIRS rating over 80% of the time.\",\"PeriodicalId\":230582,\"journal\":{\"name\":\"2018 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)\",\"volume\":\"519 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIPR.2018.8707423\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIPR.2018.8707423","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automated Video Interpretability Assessment using Convolutional Neural Networks
A neural network used to automate assessment of video quality, as measured by the Video National Imagery Interpretability Rating Scale (VNIIRS), was able to ascertain the exact VNIIRS rating over 80% of the time.
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