A Superpixel-Based Relational Auto-Encoder for Feature Extraction of Hyperspectral Images

A Superpixel-Based Relational Auto-Encoder for Feature Extraction of Hyperspectral Images

Filter banks transferred from a pre-trained deep convolutional network exhibit significant performance in heightening the inter-class separability for hyperspectral image feature extraction, but weakening the intra-class consistency simultaneously. In this paper, we propose a new superpixel-based re...

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Bibliographic Details
Main Authors: Miaomiao Liang, Licheng Jiao, Zhe Meng
Format: Article
Language:English
Published: MDPI AG 2019-10-01
Series:Remote Sensing
Subjects:
hyperspectral images classification (hsic)
convolutional neural network (cnn)
relational auto-encoder (rae)
transfer learning
superpixel
feature fusion
Online Access:https://www.mdpi.com/2072-4292/11/20/2454

Internet

https://www.mdpi.com/2072-4292/11/20/2454

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