{"title":"Remote sensing image segmentation model based on attention mechanism","authors":"Hanting Wang","doi":"10.1109/aemcse55572.2022.00086","DOIUrl":null,"url":null,"abstract":"Remote sensing images are often very large in size, which is difficult to put into GPU for training. Previous work proposed models of global and local branches. On the basis of this model, we add attention mechanism to make feature integration more complete. The results show that our method works well.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/aemcse55572.2022.00086","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
Remote sensing images are often very large in size, which is difficult to put into GPU for training. Previous work proposed models of global and local branches. On the basis of this model, we add attention mechanism to make feature integration more complete. The results show that our method works well.