Image Captioning- Bangladesh’s Heritage Perspective using Deep Learning

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dc.contributor.advisorDr. Rashedur M. Rahman
dc.contributor.authorSarowar Alam
dc.contributor.authorNishat Shamila
dc.contributor.authorKhalidul Islam
dc.contributor.authorZiaur Rahman Sovon
dc.contributor.id1812669042
dc.contributor.id1811453042
dc.contributor.id1731321642
dc.contributor.id1721673042
dc.coverage.departmentElectrical and Computer Engineering
dc.date.accessioned2024-05-09
dc.date.accessioned2024-05-09T08:09:18Z
dc.date.available2024-05-09T08:09:18Z
dc.date.issued2022
dc.description.abstractImage captioning aims to make a textual short explanation of a given image. Despite the fact that it looks to be a straightforward task, for people, it is difficult for computers since it involves the ability to analyze the image (computer vision) and provide a human-like description (natural language understanding). Encoder Decoder architectures have recently reached advanced outcomes in the form of picture captioning. In the three model datasets: Flickr_data, Flickr8k_token.txt, we provide our model with the training with which it can create captions from the images which relate to Bangladeshi culture, tradition and historical places. Bangladesh is enriched with great culture; many heritage pictures and cultural programmes attract travelers to visit our country. We try to relate our culture, place, food, and many more with machine learning to reach them with appropriate captioning and spread knowledge a little more about our culture through pictures. Our image captioning tool can be very helpful for travel lovers who want to know more about Bangladesh.
dc.description.degreeUndergraduate
dc.identifier.cd600000061
dc.identifier.print-thesisTo be assigned
dc.identifier.urihttps://repository.northsouth.edu/handle/123456789/640
dc.language.isoen_US
dc.publisherNorth South University
dc.rights© NSU Library
dc.subjectTECHNOLOGY::Electrical engineering, electronics and photonics::Electrical engineering
dc.titleImage Captioning- Bangladesh’s Heritage Perspective using Deep Learning
dc.typeProject
oaire.citation.endPage36
oaire.citation.startPage1
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