Morphological Convolutional Neural Networks for Hyperspectral Image Classification

Morphological Convolutional Neural Networks for Hyperspectral Image Classification

Convolutional neural networks (CNNs) have become quite popular for solving many different tasks in remote sensing data processing. The convolution is a linear operation, which extracts features from the input data. However, nonlinear operations are able to better characterize the internal relationsh...

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Bibliographic Details
Main Authors: Swalpa Roy, Ranjan Mondal, Mercedes E. Paoletti, Juan M. Haut, Antonio Plaza
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Classification
convolutional neural networks (CNNs)
deep learning (DL)
hyperspectral images (HSIs)
latent feature space transfer
morphological transformations
Online Access:https://ieeexplore.ieee.org/document/9451651/

Internet

https://ieeexplore.ieee.org/document/9451651/

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