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Enhanced Se-Resnet 101 For Food Image Segmentation

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dc.contributor.authorSuhaila Farhan Ahmad Abuowaida
dc.date.accessioned2024-03-12T00:43:45Z
dc.date.available2024-03-12T00:43:45Z
dc.date.issued2022-12
dc.description.abstractIn recent years, deep learning has demonstrated its usefulness and capability in computer vision due to its high accuracy and acceptability. This thesis focuses on the enhanced instance segmentation method for multiple types of food and the improved food volume estimation method for better food calorie estimation.
dc.identifier.urihttps://erepo.usm.my/handle/123456789/18583
dc.subjectEnhanced Se-Resnet 101
dc.subjectFood Image Segmentation
dc.titleEnhanced Se-Resnet 101 For Food Image Segmentation
dc.typeResource Types::text::thesis::doctoral thesis
dspace.entity.typePublication
oairecerif.author.affiliationUniversiti Sains Malaysia
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Pusat Pengajian Sains Komputer - Tesis