基于变压器的遥感自然场景分类集合深度学习方法

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

International Journal of Remote Sensing Pub Date : 2024-05-03 DOI:10.1080/01431161.2024.2343141

Arrun Sivasubramanian, Prashanth VR, Sowmya V, Vinayakumar Ravi

引用次数: 0

摘要

超高分辨率（VHR）遥感（RS）图像分类对于详细的地球表面分析至关重要。从 VHR 自然场景中提取特征至关重要，但这也是一项挑战。

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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Transformer based ensemble deep learning approach for remote sensing natural scene classification

Very high resolution (VHR) remote sensing (RS) image classification is paramount for detailed Earth’s surface analysis. Feature extraction from VHR natural scenes is crucial, but it becomes a chall...

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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).