Hierarchical Shrinkage Multiscale Network for Hyperspectral Image Classification With Hierarchical Feature Fusion

Hierarchical Shrinkage Multiscale Network for Hyperspectral Image Classification With Hierarchical Feature Fusion

Recently, deep learning (DL)-based hyperspectral image classification (HSIC) has attracted substantial attention. Many works based on the convolutional neural network (CNN) model have been certificated to be significantly successful for boosting the performance of HSIC. However, most of these method...

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Bibliographic Details
Main Authors: Hongmin Gao, Zhonghao Chen, Chenming Li
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Convolutional neural network (CNN)
hierarchical feature fusion (HFF)
hierarchical shrinkage multiscale network (HSMSN)
hyperspectral image classification (HSIC)
multidepth and multiscale residual block (MDMSRB)
Online Access:https://ieeexplore.ieee.org/document/9440750/

Internet

https://ieeexplore.ieee.org/document/9440750/

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