利用新的传输方法实现通道自适应 CVFCN，用于 PolSAR 地形分类

IF 3 3区地球科学 Q2 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY

International Journal of Remote Sensing Pub Date : 2024-08-30 DOI:10.1080/01431161.2024.2391101

Wen Xie, Tongjie Li, Hongyue Sun

引用次数: 0

摘要

本文主要解决 PolSAR 图像分类中标签数据缺乏和数据利用率不足的问题。我们提出了一种基于信道自适应的复值全卷积网络。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Channel adaptive CVFCN using a new transfer method for PolSAR terrain classification

This paper mainly addresses the lack of labelled data and insufficient data utilization in PolSAR image classification. We propose a channel adaptive Complex-Valued Fully Convolutional Networks bas...

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来源期刊

International Journal of Remote Sensing 工程技术-成像科学与照相技术

CiteScore

7.00

自引率

5.90%

发文量

219

审稿时长

4.8 months

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).