Spatial attention module.

<div><p>Hyperspectral Images (HSI) classification is a challenging task due to a large number of spatial-spectral bands of images with high inter-similarity, extra variability classes, and complex region relationships, including overlapping and nested regions. Classification becomes a co...

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Bibliographic Details
Main Author:	Mahmood Ashraf (18340154) (author)
Other Authors:	Raed Alharthi (18340157) (author), Lihui Chen (1597015) (author), Muhammad Umer (1989400) (author), Shtwai Alsubai (17019126) (author), Ala Abdulmajid Eshmawi (18340160) (author)
Published:	2024
Subjects:	Biotechnology Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified rank frequency features indian pines demonstrate indian pines dataset extra variability classes convolutional neural networks cnn methods offer challenging task due 25 &# 215 large capacity size innovative approach called complex region relationships cdc method leverages hsi data classification hsi classification methods spectral features maps method compared large number feature maps complex problem alternative approach classification becomes wise concatenation utilizing pixel spectral dimensions spectral bands pavia university overall accuracy nested regions manipulating information including state including overlapping high inter gained popularity feature tuning experimental results dense strategy computational complexity benchmark datasets art techniques
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Spatial attention module.

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