{"title":"推进高分辨率遥感：一种紧凑而强大的语义分割方法","authors":"Hua Zhang, Zhengang Jiang, Jun Xu, Xin Pan","doi":"10.1080/01431161.2024.2398226","DOIUrl":null,"url":null,"abstract":"Deep learning (DL)-based approaches are notable for their ability to establish feature associations without relying on physical constraints, unlike traditional strategies that are complex and depen...","PeriodicalId":14369,"journal":{"name":"International Journal of Remote Sensing","volume":"9 1","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advancing high-resolution remote sensing: a compact and powerful approach to semantic segmentation\",\"authors\":\"Hua Zhang, Zhengang Jiang, Jun Xu, Xin Pan\",\"doi\":\"10.1080/01431161.2024.2398226\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Deep learning (DL)-based approaches are notable for their ability to establish feature associations without relying on physical constraints, unlike traditional strategies that are complex and depen...\",\"PeriodicalId\":14369,\"journal\":{\"name\":\"International Journal of Remote Sensing\",\"volume\":\"9 1\",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Remote Sensing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/01431161.2024.2398226\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/01431161.2024.2398226","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY","Score":null,"Total":0}
Advancing high-resolution remote sensing: a compact and powerful approach to semantic segmentation
Deep learning (DL)-based approaches are notable for their ability to establish feature associations without relying on physical constraints, unlike traditional strategies that are complex and depen...
期刊介绍：
The International Journal of Remote Sensing ( IJRS) is concerned with the theory, science and technology of remote sensing and novel applications of remotely sensed data. The journal’s focus includes remote sensing of the atmosphere, biosphere, cryosphere and the terrestrial earth, as well as human modifications to the earth system. Principal topics include:
• Remotely sensed data collection, analysis, interpretation and display.
• Surveying from space, air, water and ground platforms.
• Imaging and related sensors.
• Image processing.
• Use of remotely sensed data.
• Economic surveys and cost-benefit analyses.
• Drones Section: Remote sensing with unmanned aerial systems (UASs, also known as unmanned aerial vehicles (UAVs), or drones).
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
