Spectrally Segmented-Enhanced Neural Network for Precise Land Cover Object Classification in Hyperspectral Imagery

The paradigm shift brought by deep learning in land cover object classification in hyperspectral images (HSIs) is undeniable, particularly in addressing the intricate 3D cube structure inherent in HSI data. Leveraging convolutional neural networks (CNNs), despite their architectural constraints, off...

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Auteurs principaux:	Touhid Islam, Rashedul Islam, Palash Uddin, Anwaar Ulhaq
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2024-02-01
Collection:	Remote Sensing
Sujets:	segmentation convolutional neural network hyperspectral image (HSI) support vector machine (SVM) factor analysis (FA) multi-layer CNN
Accès en ligne:	https://www.mdpi.com/2072-4292/16/5/807
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