Random Shuffling Data for Hyperspectral Image Classification with Siamese and Knowledge Distillation Network

Random Shuffling Data for Hyperspectral Image Classification with Siamese and Knowledge Distillation Network

Hyperspectral images (HSIs) are characterized by hundreds of spectral bands. The goal of HSI is to associate the pixel with a corresponding category label by analyzing subtle differences in the spectrum. Due to their excellent local context modeling capabilities, Convolutional Neural Network (CNN)-b...

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Bibliographic Details
Main Authors: Zhen Yang, Ying Cao, Xin Zhou, Junya Liu, Tao Zhang, Jinsheng Ji
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Remote Sensing
Subjects:
patch-data-based CNN method
local contextual information
random shuffling strategy
network SKDN consists of two sub-branches
HSI classification
Online Access:https://www.mdpi.com/2072-4292/15/16/4078

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