Simulated Annealing-Based Hyperspectral Data Optimization for Fish Species Classification: Can the Number of Measured Wavelengths Be Reduced?

Relative to standard red/green/blue (RGB) imaging systems, hyperspectral imaging systems offer superior capabilities but tend to be expensive and complex, requiring either a mechanically complex push-broom line scanning method, a tunable filter, or a large set of light emitting diodes (LEDs) to coll...

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Detalles Bibliográficos
Autores principales:	John Chauvin, Ray Duran, Kouhyar Tavakolian, Alireza Akhbardeh, Nicholas MacKinnon, Jianwei Qin, Diane E. Chan, Chansong Hwang, Insuck Baek, Moon S. Kim, Rachel B. Isaacs, Ayse Gamze Yilmaz, Jiahleen Roungchun, Rosalee S. Hellberg, Fartash Vasefi
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	classification hyperspectral imaging food fraud simulated annealing machine learning spectroscopy Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/fd18c1a6f0454c0ca3a24a360fcbaa59
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Simulated Annealing-Based Hyperspectral Data Optimization for Fish Species Classification: Can the Number of Measured Wavelengths Be Reduced?

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