{"title":"用于高光谱图像分类的具有细节保护功能的快速超图神经网络","authors":"Feilong Cao, Jieqin Bao, Bing Yang, Hailiang Ye","doi":"10.1080/01431161.2024.2343133","DOIUrl":null,"url":null,"abstract":"Hypergraph neural networks (HGNNs), extending the techniques of graph neural networks, have been applied to various fields due to their ability to capture more complex high-order node relationships...","PeriodicalId":14369,"journal":{"name":"International Journal of Remote Sensing","volume":"44 1","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A fast hypergraph neural network with detail preservation for hyperspectral image classification\",\"authors\":\"Feilong Cao, Jieqin Bao, Bing Yang, Hailiang Ye\",\"doi\":\"10.1080/01431161.2024.2343133\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hypergraph neural networks (HGNNs), extending the techniques of graph neural networks, have been applied to various fields due to their ability to capture more complex high-order node relationships...\",\"PeriodicalId\":14369,\"journal\":{\"name\":\"International Journal of Remote Sensing\",\"volume\":\"44 1\",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-04-26\",\"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/10.1080/01431161.2024.2343133\",\"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/10.1080/01431161.2024.2343133","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}
A fast hypergraph neural network with detail preservation for hyperspectral image classification
Hypergraph neural networks (HGNNs), extending the techniques of graph neural networks, have been applied to various fields due to their ability to capture more complex high-order node relationships...
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).
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