Deep hybrid dilated residual networks for hyperspectral image classification
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2019.11.092
Abstract: Abstract This study presents a new architecture for deep convolution networks, end-to-end hybrid dilated residual networks wherein 3D cube images are input for hyperspectral image (HSI) classification, and this is termed as 3D-2D SSHDR. The… read more here.
Keywords: classification; residual networks; hybrid dilated; dilated residual ... See more keywords
Hybrid Dilated Convolution with Multi-Scale Residual Fusion Network for Hyperspectral Image Classification
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DOI: 10.3390/mi12050545
Abstract: The convolutional neural network (CNN) has been proven to have better performance in hyperspectral image (HSI) classification than traditional methods. Traditional CNN on hyperspectral image classification is used to pay more attention to spectral features… read more here.
Keywords: network; hybrid dilated; dilated convolution; hyperspectral image ... See more keywords