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...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE journal of selected topics in applied earth observations and remote sensing Vol. 17; pp. 219 - 243
Main Authors:	Esmaeili, Mohammad, Abbasi-Moghadam, Dariush, Sharifi, Alireza, Tariq, Aqil, Li, Qingting
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	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
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!