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Assessment of forest aboveground biomass estimation from superview-1 satellite image using machine learning approaches / Azinuddin Mohd Asri
Published 2022“…In contrast, machine learning is used to calculate the accuracy assessment of dependent between independent variables. …”
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2
Spatiotemporal dynamics of vegetation cover: integrative machine learning analysis of multispectral imagery and environmental predictors
Published 2025“…In contrast, Azad Jammu and Kashmir (AJK) exhibits a more variable vegetation response, with an even higher growth rate of 0.004408 annually but a lower R² of 73.44% (p < 0.01), reflecting uneven growth across different areas. …”
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3
Detection of Denial of Service Attacks against Domain Name System Using Neural Networks
Published 2009“…In the current research for our machine learning engine, we aimed to find the optimum machine learning algorithm to be used as an IDS. …”
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4
Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach
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Decision tree and rule-based classification for predicting online purchase behavior in Malaysia / Maslina Abdul Aziz, Nurul Ain Mustakim and Shuzlina Abdul Rahman
Published 2024“…The performance of six machine learning models comprising J48, Random Tree, REPTree representing decision trees and JRip, PART, and OneR as rule-based algorithms was assessed. …”
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6
Zero distortion-based steganography for handwritten signature
Published 2018“…In this thesis, the human handwritten signature is introduced as a novel cover media (c) in conjunction with a steganography algorithm since there is a level of variability (i.e intra-user variability) within handwritten signature samples of an individual. …”
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7
Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease
Published 2021“…As the ALOS PALSAR-2 image was evaluated with dual-polarization (HH and HV), each digitized point has two distinct backscatter data with four severity levels (T0 to T3). The machine learning algorithm consistently performs well when presented with a well-balanced dataset. …”
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