ResMorCNN Model: Hyperspectral Images Classification Using Residual-Injection Morphological Features and 3DCNN Layers

Hyperspectral imagery is widely used for analyzing substances and objects, specifically focusing on their classification. The advancement of processing capabilities and the emergence of cloud computing platforms have made deep learning (DL) models increasingly popular for accurately and efficiently...

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Vydáno v:	IEEE journal of selected topics in applied earth observations and remote sensing Ročník 17; s. 219 - 243
Hlavní autoři:	Esmaeili, Mohammad, Abbasi-Moghadam, Dariush, Sharifi, Alireza, Tariq, Aqil, Li, Qingting
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	3-D convolution neural network (3DCNN) Accuracy Classification Cloud computing Convolution Data mining Data models Datasets Deep learning deep learning (DL) Effectiveness Feature extraction hyperspectral image (HSI) Hyperspectral imaging Image classification Image processing Information processing Machine learning Mathematical models Mathematics Morphology Noise reduction residual connection Shape spatial-spectral morphological features (SSMF) Three dimensional models Three-dimensional displays
ISSN:	1939-1404, 2151-1535
On-line přístup:	Získat plný text
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