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  Published Paper Details:

  Paper Title

Image Classification in Few-Shot Learning through Model-Agnostic Meta Learning (MAML)

  Authors

  Sabiha Khatoon,  Dr. Mohd Akbar

  Keywords

Image classification, Few-shot learning, MAML, Meta learning.

  Abstract


This research highlights the potential of MAML in developing intelligent image classification systems that can perform reliably in data-constrained environments. The findings contribute to the growing body of work in meta-learning and its practical applicability in computer vision, especially in domains like medical imaging, wildlife monitoring, and security surveillance where annotated data is often limited.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2504547

  Paper ID - 282166

  Page Number(s) - e717-e726

  Pubished in - Volume 13 | Issue 4 | April 2025

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Sabiha Khatoon,  Dr. Mohd Akbar,   "Image Classification in Few-Shot Learning through Model-Agnostic Meta Learning (MAML)", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 4, pp.e717-e726, April 2025, Available at :http://www.ijcrt.org/papers/IJCRT2504547.pdf

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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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