Political-advertisement video classification using deep learning methods

dc.contributor.advisor Adisak . Sukul
dc.contributor.advisor Wallapak . Tavanapong
dc.contributor.author Dhakal, Aashish
dc.contributor.department Computer Science
dc.date 2020-02-12T22:54:20.000
dc.date.accessioned 2020-06-30T03:20:04Z
dc.date.available 2020-06-30T03:20:04Z
dc.date.copyright Sun Dec 01 00:00:00 UTC 2019
dc.date.embargo 2001-01-01
dc.date.issued 2019-01-01
dc.description.abstract <p>Today’s digital world consists of vast multimedia contents: images, audios and videos. Thus, the availability of huge video datasets have encouraged researchers to design video classification techniques to group videos into categories of interest. One of the topics of interest to political scientists is automated classification of a video advertisement into a political campaign ad category or others. Recent years have seen a plethora of deep learning-based methods for image and video classification. These methods learn feature representation from the training data along with the classification model. We investigate the effectiveness of three recent deep-learning based video classification techniques for the political video advertisement classification. The best technique among the three yields an accuracy of 80%. In this thesis, we further improve the classification accuracy by combining the results of classification of text features with that of the best deep learning methods we studied. Our method achieves the classification accuracy of 91%.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/etd/17668/
dc.identifier.articleid 8675
dc.identifier.contextkey 16524605
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath etd/17668
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/31851
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/etd/17668/Dhakal_iastate_0097M_18428.pdf|||Fri Jan 14 21:27:00 UTC 2022
dc.subject.disciplines Computer Sciences
dc.subject.keywords Deep Learning
dc.subject.keywords Political Advertisement
dc.subject.keywords Video Classification
dc.title Political-advertisement video classification using deep learning methods
dc.type article
dc.type.genre thesis
dspace.entity.type Publication
relation.isOrgUnitOfPublication f7be4eb9-d1d0-4081-859b-b15cee251456
thesis.degree.discipline Computer Science
thesis.degree.level thesis
thesis.degree.name Master of Science
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