基于分段 PCA 和利用多分支特征融合的 3D-2D CNN 的有效高光谱图像分类

IF 1 4区地球科学 Q4 GEOGRAPHY, PHYSICAL

Journal of Spatial Science Pub Date : 2024-01-30 DOI:10.1080/14498596.2024.2305119

Masud Ibn Afjal, Md. Nazrul Islam Mondal, Md. Al Mamun

引用次数: 0

摘要

我们提出了一种创新的高光谱图像（HSI）分类方法，以应对波长带间隔较近所带来的挑战。我们的方法结合了 3D-2D 卷积神经网络（C...

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Effective hyperspectral image classification based on segmented PCA and 3D-2D CNN leveraging multibranch feature fusion

We present an innovative hyperspectral image (HSI) classification method addressing challenges posed by closely spaced wavelength bands. Our approach combines 3D-2D convolutional neural networks (C...

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来源期刊

Journal of Spatial Science 地学-地质学

CiteScore

5.00

自引率

5.30%

发文量

审稿时长

>12 weeks

期刊介绍： The Journal of Spatial Science publishes papers broadly across the spatial sciences including such areas as cartography, geodesy, geographic information science, hydrography, digital image analysis and photogrammetry, remote sensing, surveying and related areas. Two types of papers are published by he journal: Research Papers and Professional Papers. Research Papers (including reviews) are peer-reviewed and must meet a minimum standard of making a contribution to the knowledge base of an area of the spatial sciences. This can be achieved through the empirical or theoretical contribution to knowledge that produces significant new outcomes. It is anticipated that Professional Papers will be written by industry practitioners. Professional Papers describe innovative aspects of professional practise and applications that advance the development of the spatial industry.