Mohammed Zerara
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The aim of this project is to detect Enterobacter sakazakii bacteria in powder infant formula milk using Raman spectroscopy. Machine learning and deep learning algorithms have been used to detect the presence of enterobacter sakazakii. Deep learning algorithms did not require prior pre-processing for background removal nor spectra smoothing.<\/p>","value":null,"finished":false,"pilier":6,"url":null,"keywords":null,"disciplines":[],"axes":[],"partners":[{"id":247505,"name":"Prof. Han Chun","confidential":false,"types":[{"id":7,"code":"PA"}],"institution":"Beijing Institute of Technology, China","class":"academique"}],"collaborators":[{"id":1209482,"role":"PA","display":true,"displayRole":true,"displayFinancialPartner":false,"displayAcademicPartner":false,"displayProfessionalPartner":false,"collaborator":"mohammed.zerara","project":1006201}],"dataHub":false,"startAt":"2022-03-01T00:00:00+01:00","endAt":"2023-06-30T00:00:00+02:00","fundingSource":"Beijing Institute of Technology, China","publications":[],"projectUrl":null,"repo_name":null}}
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The aim of this project is to exploit hyperspectral imaging for features detection in compounds and products (food, biological samples). Machine learning methods are used to perform binary and multi-label classification, as well as anomaly detection.<\/p>","value":null,"finished":false,"pilier":6,"url":null,"keywords":null,"disciplines":[],"axes":[],"partners":[],"collaborators":[{"id":1059197,"role":"ME","display":true,"displayRole":true,"displayFinancialPartner":true,"displayAcademicPartner":true,"displayProfessionalPartner":true,"collaborator":"mohammed.zerara","project":1018786}],"dataHub":false,"startAt":null,"endAt":null,"fundingSource":"The project is funded by an international organization.","publications":[],"projectUrl":null,"repo_name":null}}
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