Convolutional Neural Network

  • Unique Paper ID: 189486
  • Volume: 12
  • Issue: 9
  • PageNo: 2854-2855
  • Abstract:
  • Convolutional Neural Network forms the base of all computer vision applications. Uses like self-driving cars, object recognition, face recognition, etc. Simple neural networks struggle with images because they are slow at training and processing and have a large number of parameters. To overcome these issues, we use Convolutional Neural Networks.

Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{189486,
        author = {Shrutika Adole and Prof. K. P. Barabde},
        title = {Convolutional Neural Network},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {2854-2855},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=189486},
        abstract = {Convolutional Neural Network forms the base of all computer vision applications. Uses like self-driving cars, object recognition, face recognition, etc. Simple neural networks struggle with images because they are slow at training and processing and have a large number of parameters. To overcome these issues, we use Convolutional Neural Networks.},
        keywords = {Convolutional Neural Networks, Deep Learning, Image Classification, Feature Extraction, Neural Architecture, Artificial Intelligence, Computer Vision, Deep Neural Networks, Image Processing, Machine Learning, Machine Vision, Pattern},
        month = {February},
        }

Cite This Article

Adole, S., & Barabde, P. K. P. (2026). Convolutional Neural Network. International Journal of Innovative Research in Technology (IJIRT), 12(9), 2854–2855.

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