Divide-and-Conquer Dual-Architecture Convolutional Neural Network for Classification of Hyperspectral Images

Divide-and-Conquer Dual-Architecture Convolutional Neural Network for Classification of Hyperspectral Images

Convolutional neural network (CNN) is well-known for its powerful capability on image classification. In hyperspectral images (HSIs), fixed-size spatial window is generally used as the input of CNN for pixel-wise classification. However, single fixed-size spatial architecture hinders the excellent p...

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Bibliographic Details
Main Authors: Jie Feng, Lin Wang, Haipeng Yu, Licheng Jiao, Xiangrong Zhang
Format: Article
Language:English
Published: MDPI AG 2019-02-01
Series:Remote Sensing
Subjects:
Hyperspectral image classification
divide-and-conquer
dual-architecture convolutional neural network
homogeneous and heterogeneous regions
superpixel segmentation
Online Access:https://www.mdpi.com/2072-4292/11/5/484

Internet

https://www.mdpi.com/2072-4292/11/5/484

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