Publication:
A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification

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dc.citedby0
dc.contributor.authorMadanan M.en_US
dc.contributor.authorGunasekaran S.S.en_US
dc.contributor.authorMahmoud M.A.en_US
dc.contributor.authorid57203784027en_US
dc.contributor.authorid55652730500en_US
dc.contributor.authorid55247787300en_US
dc.date.accessioned2024-10-14T03:19:21Z
dc.date.available2024-10-14T03:19:21Z
dc.date.issued2023
dc.description.abstractImage classification is a popular and important area of image processing research in today's society. For machine learning, SVM is a very good classification model. CNN is a type of convolution neural network that has an unpredictable development and uses convolution calculations. It is one of the most well-known deep learning algorithms. This review thinks about and inspects exemplary AI and profound learning picture classification procedures involving SVM and CNN as specific illustrations. Using a large sample mnist dataset, this study found that CNN has an accuracy of 0.97 and SVM has an accuracy of 0.89en_US
dc.description.abstractSVM has an accuracy of 0.85 and CNN has an accuracy of 0.82 when working with a small sample ImageNet dataset. Tests in this review show that for little example informational collections, standard ML has an improved arrangement impact than deep learning structure does. � 2023 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1109/IC3I59117.2023.10398030
dc.identifier.epage2439
dc.identifier.scopus2-s2.0-85187300318
dc.identifier.spage2436
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85187300318&doi=10.1109%2fIC3I59117.2023.10398030&partnerID=40&md5=db61abffb0c90ade269079af699993f1
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/34374
dc.pagecount3
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitleProceedings of International Conference on Contemporary Computing and Informatics, IC3I 2023
dc.subjectdeep learning
dc.subjectimage classification
dc.subjectmachine learning
dc.subjectConvolution
dc.subjectConvolutional neural networks
dc.subjectDeep learning
dc.subjectLarge datasets
dc.subjectLearning algorithms
dc.subjectLearning systems
dc.subjectSupport vector machines
dc.subjectClassification models
dc.subjectClassification procedure
dc.subjectComparative analyzes
dc.subjectConvolution neural network
dc.subjectDeep learning
dc.subjectImages classification
dc.subjectImages processing
dc.subjectMachine-learning
dc.subjectSmall samples
dc.subjectStandard ML
dc.subjectImage classification
dc.titleA Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classificationen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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