Hyperspectral unmixing of autoencoder based on attention and total variation

被引：0

作者：

Wang, Ying ^{[1
,2
]}

Zhang, Mingbo ^{[3
]}

Zuo, Fang ^{[4
,5
]}

机构：

[1] Institute of Intelligence Networks System, Henan University, Henan, Kaifeng, China

[2] Henan Experimental Teaching Demonstration Centre of Modern Network Technology, Henan University, Henan, Kaifeng, China

[3] Intelligent Data Processing Engineering Research Center of Henan Province, Henan University, Henan, Kaifeng, China

[4] Henan International Joint Laboratory of Theories and Key Technologies on Intelligence Networks, Henan University, Henan, Kaifeng, China

[5] Subject Innovation and Intelligence Introduction Base of Henan Higher Educational Institution - Intelligent Information Processing Innovation and Intelligence Introduction Base of Henan University Software Engineering, Henan University, Henan, Kaifeng, Chi

来源：

Proceedings of SPIE - The International Society for Optical Engineering | 2022年 / 12328卷

关键词：

Engineering Village;

D O I：

123280B

中图分类号：

学科分类号：

摘要：

Attention - Attention mechanisms - Auto encoders - Deep learning - Hidden layers - Hyperspectral unmixing - Learning process - Low dimensional - Total-variation - Unmixing

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