Show simple item record

Cassava Leaf Disease Classification with Deep Learning

dc.contributor.authorEffiong, Blessing Uduakobong
dc.date.accessioned2022-02-02T09:39:16Z
dc.date.available2022-02-02T09:39:16Z
dc.date.issued2021-08-13
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/123456789/5019
dc.description2021 Computer Science Masters Thesesen_US
dc.description.abstractInspired by the current trend in artificial intelligence and neural network research, and with the increase in accuracy of models with deep neural network architecture (DNN), our work is dedicated to developing and training a deep neural network to extract meaningful patterns of diseases from leaves. We show how DNNs are applied to classification problems – classifying cassava leaf disease with a form of advanced convolutional neural networks with compound scaling (Efficient Nets) using supervised learning approach.en_US
dc.description.sponsorshipAUSTen_US
dc.language.isoenen_US
dc.publisherAUSTen_US
dc.subjectEffiong Blessing Uduakobongen_US
dc.subjectProf Csató Lehelen_US
dc.subjectCassava Leaf Disease Classification With Deep Learningen_US
dc.subject2021 Computer Science Masters Thesesen_US
dc.titleCassava Leaf Disease Classification with Deep Learningen_US
dc.typeThesisen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

  • Computer Science105

    This collection contains Computer Science Student's Theses from 2009-2022

Show simple item record