Attention-Aware Pseudo-3-D Convolutional Neural Network for Hyperspectral Image Classification

Convolutional neural networks (CNNs) have been applied for hyperspectral image classification recently. Among this class of deep models, 3-D CNN has been shown to be more effective by learning discriminative features from abundant spectral signatures and spatial contexts in hyperspectral imagery (HS...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing 2021-09, Vol.59 (9), p.7790-7802
Hauptverfasser:	Lin, Jianzhe, Mou, Lichao, Zhu, Xiao Xiang, Ji, Xiangyang, Wang, Z. Jane
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Classification Convolution Dimensions Feature extraction Feature maps Hyperspectral image Hyperspectral imaging Image classification Imagery Neural networks Pipelines salient samples Solid modeling Spectral signatures Submarine pipelines supervised classification Task analysis Three dimensional models transfer learning Urban agriculture
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