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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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| I publikationen: | Sensors (Basel) |
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| Huvudupphovsmän: | , , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
MDPI
2021
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8037346/ https://ncbi.nlm.nih.gov/pubmed/33805937 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s21072293 |
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