A Novel Multi-Objective Binary Chimp Optimization Algorithm for Optimal Feature Selection: Application of Deep-Learning-Based Approaches for SAR Image Classification

Removing redundant features and improving classifier performance necessitates the use of meta-heuristic and deep learning (DL) algorithms in feature selection and classification problems. With the maturity of DL tools, many data-driven polarimetric synthetic aperture radar (POLSAR) representation mo...

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Vydané v:	Sensors (Basel, Switzerland) Ročník 23; číslo 3; s. 1180
Hlavní autori:	Sadeghi, Fatemeh, Larijani, Ata, Rostami, Omid, Martín, Diego, Hajirahimi, Parisa
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland MDPI AG 19.01.2023 MDPI
Predmet:	Accuracy Algorithms Artificial satellites in remote sensing Classification deep convolutional neural network Feature selection Heuristic improved chimp optimization algorithm Machine learning Mathematical optimization Methods Neural networks POLSAR image classification Remote sensing systems Support vector machines Synthetic aperture radar Urban areas improved chimp optimization algorithm deep convolutional neural network POLSAR image classification feature selection
ISSN:	1424-8220, 1424-8220
On-line prístup:	Získať plný text
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