Towards devising an efficient VQA in the Bengali Language

dc.contributor.advisorNoor, Jannatun
dc.contributor.authorIslam, S M Shahriar
dc.contributor.authorAuntor, Riyad Ahsan
dc.contributor.authorIslam, Minhajul
dc.contributor.authorChowdhury, Tahmin Haider
dc.contributor.authorHossain Anik, Mohammad Yousuf
dc.date.accessioned2022-11-21T04:53:02Z
dc.date.available2022-11-21T04:53:02Z
dc.date.issued2021-12
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 50-53).
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2021.
dc.description.abstractThis paper aims to provide insight into how Visual question answering might work on Bangla datasets versus English datasets. Several studies have been conducted on deep learning methods applied to Bangla datasets up to this point. However, a Bangla dataset with images and questions embedded in each of them has yet to be created. We attempted to create a Bangla dataset suitable for such implementation through our re search. The step-by-step procedures in our work demonstrate how various bar riers can be overcome while developing datasets. We attempted to use existing visual question answering datasets because there are no actual Bangla datasets created for this specific task.In the end we successfully created our own Bangla visual question an swering datasets and proposed a model to train and compare among existing datasets. Following that, the comparison was provided to show how the Bangla dataset differs from the English datasets in terms of the VQA model. Our work should make more than enough room for future research and implementation of visual question answering tasks in Bangla.
dc.identifier.otherID: 18101456
dc.identifier.otherID: 18101358
dc.identifier.otherID: 18101304
dc.identifier.otherID: 18101056
dc.identifier.otherID: 18101586
dc.identifier.otherhttps://dspace.bracu.ac.bd/server/api/core/items/cc8b3bcc-aac5-4932-a2fe-ec6c689f9112
dc.identifier.urihttp://hdl.handle.net/10361/17594
dc.language.isoen_US
dc.publisherBRAC University
dc.sourceBRAC University Institutional Repository
dc.subjectNatural Language Processing
dc.subjectCLEVR
dc.subjectVQA V1
dc.subjectVisual Question Answering
dc.titleTowards devising an efficient VQA in the Bengali Language
dc.typeThesis

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
18101456, 18101358, 18101304, 18101056, 18101586_CSE.pdf
Size:
5.36 MB
Format:
Adobe Portable Document Format