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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16373
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dc.contributor.authorSharma, Yashvardhan-
dc.date.accessioned2024-11-14T09:22:46Z-
dc.date.available2024-11-14T09:22:46Z-
dc.date.issued2021-
dc.identifier.urihttps://www.taylorfrancis.com/chapters/edit/10.1201/9781003102380-9/visual-question-answering-system-using-integrated-models-image-captioning-bert-lavika-goel-mohit-dhawan-rachit-rathore-satyansh-rai-aaryan-kapoor-yashvardhan-sharma-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16373-
dc.description.abstractVisual question and answering (VQA) is a task that involves taking input as an image and a natural question about it to generate output of an answer to that question. This is a multidisciplinary problem: it includes problems faced in computer vision and natural language processing. This chapter uses a combination of network architectures of question answering (BERT) and image captioning (BUTD, show-and-tell model, CaptionBot, and show, attend, and tell model) models for VQA tasks. The chapter also highlights the comparison between these four VQA models.en_US
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.subjectComputer Scienceen_US
dc.subjectVisual question and answering (VQA)en_US
dc.subjectBERTen_US
dc.subjectBUTDen_US
dc.titleVisual Question-Answering System Using Integrated Models of Image Captioning and BERTen_US
dc.typeArticleen_US
Appears in Collections:Department of Computer Science and Information Systems

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