Land-Use and Land-Cover Classification Using a Human Group-Based Particle Swarm Optimization Algorithm with an LSTM Classifier on Hybrid Pre-Processing Remote-Sensing Images

Land-Use and Land-Cover Classification Using a Human Group-Based Particle Swarm Optimization Algorithm with an LSTM Classifier on Hybrid Pre-Processing Remote-Sensing Images

Land-use and land-cover (LULC) classification using remote sensing imagery plays a vital role in many environment modeling and land-use inventories. In this study, a hybrid feature optimization algorithm along with a deep learning classifier is proposed to improve the performance of LULC classificat...

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Bibliographic Details
Main Authors: R. Ganesh Babu, K. Uma Maheswari, C. Zarro, B.D. Parameshachari, S.L. Ullo
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Remote Sensing
Subjects:
land-use and land-cover classification
Haralick texture feature
histogram of oriented gradient
human group optimization
local gabor binary pattern histogram sequence
long short term memory network
Online Access:https://www.mdpi.com/2072-4292/12/24/4135

Internet

https://www.mdpi.com/2072-4292/12/24/4135

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