Multimodal Attention Variants for Visual Question Answering

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dc.contributor.authorMishra, Aakansha
dc.date.accessioned2023-12-18T06:36:22Z
dc.date.available2023-12-18T06:36:22Z
dc.date.issued2023
dc.descriptionSupervisors: Anand, Ashish and Guha, Prithwijiten_US
dc.description.abstractVisual Question Answering (VQA) is an exciting field of research that involves answering natural language questions asked about an image. This multimodal task requires models to understand the syntax and semantics of the question, interact with the relevant objects in the image, and infer the answer using both image and text semantics. Due to its complex behavior, VQA has gained considerable attention from both vision and natural language research community.en_US
dc.identifier.otherROLL NO.166101010
dc.identifier.urihttps://gyan.iitg.ac.in/handle/123456789/34
dc.language.isoenen_US
dc.relation.ispartofseriesTH-3229
dc.subjectDepartment of Computer Science and Engineeringen_US
dc.titleMultimodal Attention Variants for Visual Question Answeringen_US
dc.typeThesisen_US
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PhD Theses (Computer Science and Engineering)