Feature Reduction for the Classification of Bruise Damage to Apple Fruit Using a Contactless FT-NIR Spectroscopy with Machine Learning.

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作者： Jean Frederic Isingizwe,Nturambirwe ^[1] ; Eslam A,Hussein ^[2] ; Mattia,Vaccari ^[1] ; Christopher,Thron ^[2] ; Willem Jacobus,Perold ^[3] ; Umezuruike Linus,Opara ^[4]

作者单位： Eresearch Office, DVC Research and Innovation, University of the Western Cape, Private Bag X17, Bellville 7535, South Africa. ^[1] Inter-University Institute for Data Intensive Astronomy, Department of Physics and Astronomy, University of the Western Cape, Bellville 7535, South Africa. ^[2] Inter-University Institute for Data Intensive Astronomy, Department of Astronomy, University of Cape Town, Rondebosch 7701, South Africa. ^[3] Department of Science and Mathematics, Texas A&M University-Central Texas, Killeen, TX 76549, USA. ^[4] Department of Electrical and Electronic Engineering, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa. ^[5] SARChI Postharvest Technology Research Laboratory, Africa Institute for Postharvest Technology, Faculty of AgriSciences, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa. ^[6] UNESCO International Centre for Biotechnology, Nsukka 410001, Nigeria. ^[7]

关键词 apples baseline bruise damage defect classification feature reduction machine learning model optimisation quality control uncertainty quantification variable selection

DOI 10.3390/foods12010210

PMID 36613425

发布时间 2023-01-11

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Foods (Basel, Switzerland)

2023年12卷1期

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Feature Reduction for the Classification of Bruise Damage to Apple Fruit Using a Contactless FT-NIR Spectroscopy with Machine Learning.

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Feature Reduction for the Classification of Bruise Damage to Apple Fruit Using a Contactless FT-NIR Spectroscopy with Machine Learning.

Foods (Basel, Switzerland)

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Foods (Basel, Switzerland)

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