Ground object information extraction out of hyperspectral images refers to the process of identifying and characterizing different materials or objects present ...

Deep learning algorithms are applied to extract ground feature information, which is of great significance to the safety production in the mining area.

The end-member extraction method is employed to extract 25 end-member spectra of almost all lithology in the research area from the image. The similarity ...

Deep learning algorithms are applied to extract ground feature information, which is of great significance to the safety production in the mining area. The ...

Ground object information extraction from hyperspectral remote sensing images using deep learning algorithm. https://doi.org/10.1016/j.micpro.2021.104394.

This study proposes a hybrid PPDL approach for object classification for very-high-resolution satellite images.

Deep Learning (DL) techniques have demonstrated remarkable efficacy in various HSI analysis tasks, including those within agriculture.

Deep neural networks for target detection, band selection, and classification in hyperspectral images. Deep learning for surface parameters retrieval from ...

We propose a hybrid convolution transformer framework. Our method uses a vision transformer and a residual 3D convolutional neural network model.

Hyperspectral is one of such techniques, which is used mainly when the images from the satellite are captured and are used to identify different objects.