A Survey of Available Techniques for Naive Artificial Intelligence based System for Conversing with a Human

Authors

  • Rayyan Hashmi M.Tech Student, JP Institute of Engineering & Technology, Meerut, India Author
  • Ayan Rajput Assistant Professor, JP Institute of Engineering & Technology, Meerut, India Author

Keywords:

Visual Question Answering, visualqa, AI, Natural Language Processing

Abstract

Visual questions selectively target different areas of an image, including background details and underlying context. As a result, a system that succeeds at VQA typically needs a more detailed understanding of the image and complex reasoning than a system producing generic image captions. Moreover, VQA is amenable to automatic evaluation, since many open-ended answers contain only a few words or a closed set of answers that can be provided in a multiple-choice format. We provide a dataset containing ∼0.25M images, ∼0.76M questions, and ∼10M answers (www.visualqa.org), and discuss the information it provides. Numerous baselines and methods for VQA are provided and compared with human performance. ”

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Published

16-05-2024

Issue

Section

Research Articles

How to Cite

A Survey of Available Techniques for Naive Artificial Intelligence based System for Conversing with a Human. (2024). International Journal of Scientific Research in Science and Technology, 11(3), 865-876. https://ijsrst.com/index.php/home/article/view/IJSRST2411362

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