{"title":"D-FusionNet：利用扩张卷积块从遥感图像中提取道路","authors":"Ruixuan Zhang, Wu Zhu, Yankui Li, Tiansheng Song, Zhenhong Li, Wenjing Yang, Luyao Yang, Tian Zhou, Xuanyu Xu","doi":"10.1080/15481603.2023.2270806","DOIUrl":null,"url":null,"abstract":"Deep learning techniques have been applied to extract road areas from remote sensing images, leveraging their efficient and intelligent advantages. However, the contradiction between the effective ...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"68 4","pages":""},"PeriodicalIF":6.9000,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"D-FusionNet: road extraction from remote sensing images using dilated convolutional block\",\"authors\":\"Ruixuan Zhang, Wu Zhu, Yankui Li, Tiansheng Song, Zhenhong Li, Wenjing Yang, Luyao Yang, Tian Zhou, Xuanyu Xu\",\"doi\":\"10.1080/15481603.2023.2270806\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Deep learning techniques have been applied to extract road areas from remote sensing images, leveraging their efficient and intelligent advantages. However, the contradiction between the effective ...\",\"PeriodicalId\":55091,\"journal\":{\"name\":\"GIScience & Remote Sensing\",\"volume\":\"68 4\",\"pages\":\"\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2023-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"GIScience & Remote Sensing\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1080/15481603.2023.2270806\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOGRAPHY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"GIScience & Remote Sensing","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/15481603.2023.2270806","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOGRAPHY, PHYSICAL","Score":null,"Total":0}
D-FusionNet: road extraction from remote sensing images using dilated convolutional block
Deep learning techniques have been applied to extract road areas from remote sensing images, leveraging their efficient and intelligent advantages. However, the contradiction between the effective ...
期刊介绍：
GIScience & Remote Sensing publishes original, peer-reviewed articles associated with geographic information systems (GIS), remote sensing of the environment (including digital image processing), geocomputation, spatial data mining, and geographic environmental modelling. Papers reflecting both basic and applied research are published.
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