| dc.contributor.author |
Sharma, Yashvardhan |
|
| dc.date.accessioned |
2024-11-14T09:22:46Z |
|
| dc.date.available |
2024-11-14T09:22:46Z |
|
| dc.date.issued |
2021 |
|
| dc.identifier.uri |
https://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.uri |
http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16373 |
|
| dc.description.abstract |
Visual 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.iso |
en |
en_US |
| dc.publisher |
Taylor & Francis |
en_US |
| dc.subject |
Computer Science |
en_US |
| dc.subject |
Visual question and answering (VQA) |
en_US |
| dc.subject |
BERT |
en_US |
| dc.subject |
BUTD |
en_US |
| dc.title |
Visual Question-Answering System Using Integrated Models of Image Captioning and BERT |
en_US |
| dc.type |
Article |
en_US |