Hierarchical Multi-Scale Convolutional Neural Networks for Hyperspectral Image Classification

Hierarchical Multi-Scale Convolutional Neural Networks for Hyperspectral Image Classification

Deep learning models combining spectral and spatial features have been proven to be effective for hyperspectral image (HSI) classification. However, most spatial feature integration methods only consider a single input spatial scale regardless of various shapes and sizes of objects over the image pl...

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Bibliographic Details
Main Authors: Simin Li, Xueyu Zhu, Jie Bao
Format: Article
Language:English
Published: MDPI AG 2019-04-01
Series:Sensors
Subjects:
hyperspectral image (HSI) classification
convolutional neural networks (CNNs)
bidirectional LSTM
multi-scale features
Online Access:https://www.mdpi.com/1424-8220/19/7/1714

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https://www.mdpi.com/1424-8220/19/7/1714

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