Hyperspectral Classification of Blood-Like Substances Using Machine Learning Methods Combined with Genetic Algorithms in Transductive and Inductive Scenarios

Hyperspectral Classification of Blood-Like Substances Using Machine Learning Methods Combined with Genetic Algorithms in Transductive and Inductive Scenarios

This study is focused on applying genetic algorithms (GAs) to model and band selection in hyperspectral image classification. We use a forensic-inspired data set of seven hyperspectral images with blood and five visually similar substances to test GA-optimised classifiers in two scenarios: when the...

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Bibliographic Details
Main Authors: Filip Pałka, Wojciech Książek, Paweł Pławiak, Michał Romaszewski, Kamil Książek
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Sensors
Subjects:
hyperspectral classification
blood
SVM
genetic algorithm
machine learning
Online Access:https://www.mdpi.com/1424-8220/21/7/2293

Internet

https://www.mdpi.com/1424-8220/21/7/2293

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