{"title":"通过数据增强和对比学习实现无监督弱光图像增强","authors":"Shao Junzhe, Zhang Zhibin","doi":"10.1080/13682199.2024.2395751","DOIUrl":null,"url":null,"abstract":"Today, with the increasing demand for visual perception and high-level computational vision tasks, the field of low-light enhancement is rapidly developing. However, models trained on existing data...","PeriodicalId":22456,"journal":{"name":"The Imaging Science Journal","volume":"61 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unsupervised low-light image enhancement by data augmentation and contrastive learning\",\"authors\":\"Shao Junzhe, Zhang Zhibin\",\"doi\":\"10.1080/13682199.2024.2395751\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Today, with the increasing demand for visual perception and high-level computational vision tasks, the field of low-light enhancement is rapidly developing. However, models trained on existing data...\",\"PeriodicalId\":22456,\"journal\":{\"name\":\"The Imaging Science Journal\",\"volume\":\"61 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Imaging Science Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/13682199.2024.2395751\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Imaging Science Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/13682199.2024.2395751","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Unsupervised low-light image enhancement by data augmentation and contrastive learning
Today, with the increasing demand for visual perception and high-level computational vision tasks, the field of low-light enhancement is rapidly developing. However, models trained on existing data...
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
