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CNN is the most popular learning network established in the recent decades. Many variants of neural networks emerged for various applications related to image detection, recognition and classification. As images are prove input for the CNN, the CNN are more performant in machine learning and deep learning applications. CNNs are specialized in feature extraction, feature based classification. Higher the layers more intricate are the features. In this paper, enlisting various types of CNNs and the future scope is discussed.

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A Comprehensive Study on Convolution Neural Networks - Architecture, Applications and Future Scope

  • 会议论文

  • 发表日期：

    2025年

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  • S. Abdulkani,
  • M. Shereesha,
  • Nandala Narayanamma,
  • A. Jyothi Babu,
  • B. Sargunam,
  • P. Radhika Raju

摘要

CNN is the most popular learning network established in the recent decades. Many variants of neural networks emerged for various applications related to image detection, recognition and classification. As images are prove input for the CNN, the CNN are more performant in machine learning and deep learning applications. CNNs are specialized in feature extraction, feature based classification. Higher the layers more intricate are the features. In this paper, enlisting various types of CNNs and the future scope is discussed.