Learning to Pay Attention on Spectral Domain: A Spectral Attention Module-Based Convolutional Network for Hyperspectral Image Classification

Volume: 58, Issue: 1, Pages: 110 - 122
Published: Jan 1, 2020
Abstract
Over the past few years, hyperspectral image classification using convolutional neural networks (CNNs) has progressed significantly. In spite of their effectiveness, given that hyperspectral images are of high dimensionality, CNNs can be hindered by their modeling of all spectral bands with the same weight, as probably not all bands are equally informative and predictive. Moreover, the usage of useless spectral bands in CNNs may even introduce...
Paper Details
Title
Learning to Pay Attention on Spectral Domain: A Spectral Attention Module-Based Convolutional Network for Hyperspectral Image Classification
Published Date
Jan 1, 2020
Volume
58
Issue
1
Pages
110 - 122
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