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Development of Naïve Algorithm for Generation of Artificial Intelligence based System for Conversing with a Human

Author

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  • Rayyan Hashmi
  • Ayan Rajput

Abstract

We propose the task of free-form and open-ended Visual Question Answering (VQA). Given an image and a natural language question about the image, the task is to provide an accurate natural language answer. Mirroring real-world scenarios, such as helping the visually impaired, both the questions and answers are open-ended. 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.”

Suggested Citation

  • Rayyan Hashmi & Ayan Rajput, 2024. "Development of Naïve Algorithm for Generation of Artificial Intelligence based System for Conversing with a Human," International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 11(3), pages 877-893, June.
    • Handle: RePEc:etm:ijsrst:v11:y2024:i3:id:273
    DOI: 10.32628/IJSRST2411363
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