A Lightweight Convolutional Neural Network for Hyperspectral Image Classification

IEEE Transactions on Geoscience and Remote Sensing(2021)

Cited 63|Views42
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Abstract
In the hyperspectral image, each pixel corresponds to a small area on the Earth’s surface and represents the intrinsic characteristic of objects, which can be applied for recognition of land covers. Nevertheless, hyperspectral image processing should face some critical issues, and a small sample set problem may be the most challenging one in the research. Deep learning (DL), which has successfully...
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Key words
Hyperspectral imaging,Feature extraction,Convolution,Convolutional neural networks,Deep learning,Principal component analysis
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