Smart feature extraction and classification of hyperspectral images based on convolutional neural networks
Author:
Affiliation:
1. SETIT LaboratoryISITCom, University of SousseTunisia
2. IMT AtlantiqueISITCom, University of SousseTunisia
3. SETIT LaboratoryENIS, University of SfaxTunisia
Publisher
Institution of Engineering and Technology (IET)
Subject
Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2019.1282
Reference32 articles.
1. HaidarA. VermaB. HaidarR.: ‘A swarm based optimization of the xgboost parameters’
2. Fast and Efficient Limited Data Hyperspectral Remote Sensing Image Classification via GMM-Based Synthetic Samples
3. Analysis of various optimizers on deep convolutional neural network model in the application of hyperspectral remote sensing image classification
4. Naive gabor networks for hyperspectral image classification;Liu C.;IEEE Trans. Neural Netw. Learn. Syst.,2020
5. Gradient-based learning applied to document recognition
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