YouTube thumbnail design recommendation systems using image-tabular multimodal data for Thai’s YouTu...
YouTube thumbnail design recommendation systems using image-tabular multimodal data for Thai’s YouTube thumbnail
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Publisher
Heidelberg: Springer Nature B.V
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Language
English
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Publisher
Heidelberg: Springer Nature B.V
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Contents
This study analyzes YouTube thumbnails to identify key elements that distinguish different categories and attract viewers, specifically focusing on YouTubers in Thailand. Using a fine-tuned Convolutional Neural Network model named Xception, we classified images into food, IT, and travel categories with 88% accuracy. Object detection models identifi...
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Full title
YouTube thumbnail design recommendation systems using image-tabular multimodal data for Thai’s YouTube thumbnail
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Record Identifier
TN_cdi_proquest_journals_3101005069
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3101005069
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ISSN
1869-5450
E-ISSN
1869-5469
DOI
10.1007/s13278-024-01317-7
