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...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Sensors (Basel, Switzerland) Ročník 23; číslo 3; s. 1180
Hlavní autoři:	Sadeghi, Fatemeh, Larijani, Ata, Rostami, Omid, Martín, Diego, Hajirahimi, Parisa
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland MDPI AG 19.01.2023 MDPI
Témata:	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 přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!