Deep Learning-Based Image Extraction

Authors

  • K. S. Krupa Department of Information Science and Engineering, Global Academy of Technology, India https://orcid.org/0000-0002-8522-3793
  • Kiran Y C Department of Information Science and Engineering, Global Academy of Technology, India
  • M. Gaganakumari Department of Information Science and Engineering, Global Academy of Technology, India
  • S. R. Kavana Department of Information Science and Engineering, Global Academy of Technology, India
  • R. Meghana Department of Information Science and Engineering, Global Academy of Technology, India
  • R. Varshana Department of Information Science and Engineering, Global Academy of Technology, India

DOI:

https://doi.org/10.47852/bonviewAIA2202326

Keywords:

deep learning, content-based image retrieval, convolution neural network, VGG-16, principal component analysis

Abstract

The development of the web and advancements in computation and multimedia technologies have led to an increase in the variety of photo databases and the collection of hundreds of images that include medical images, e-libraries, and art galleries. The necessary images from that kind of big collection may demand a lengthy period to retrieve using traditional image extraction techniques like Textual Based Images Retrieval. It is essential to develop an effective image extraction procedure that can handle such vast amounts of data at once. The main objective is to develop a trustworthy tool that effectively generates, uses, and responds to data. It employs a strategy for creating an  effective picture retrieval application that enables individuals to ask questions about the software and extract it from a huge database.

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Published

2022-09-13

How to Cite

Krupa, K. S., Kiran, Y. C., Gaganakumari, M., Kavana, S. R., Meghana, R., & Varshana, R. (2022). Deep Learning-Based Image Extraction. Artificial Intelligence and Applications. https://doi.org/10.47852/bonviewAIA2202326

Issue

Section

Research Article