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Towards Convolution Neural Networks (CNNs): A Brief Overview of AI and Deep Learning

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Inventive Communication and Computational Technologies

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 89))

Abstract

Today’s era is of cutting edge of innovations as well as technologies. One of the major problems, researchers often face is an issue looking for an appropriate research area. For instance, there are numerous fields these days on which research is being carried out and to pick one out of those topics is itself a challenging task. The major objective of this review paper is to embark upon Artificial Intelligence (AI) that prompted the emergence of deep learning (DL) and further to convolution neural networks (CNNs). Limitations of CNNs that led to the development of Capsule Neural Networks (CapsNets) have been included. The significant goal of this review paper is to discuss the latest trends in which research is on-going and is still in progress. Also, the key challenges faced by past researchers are highlighted.

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Author information

Authors and Affiliations

  1. PhD Research Scholar, UIET, Panjab University, Chandigarh, 160014, India

    Preetjot Kaur

  2. Associate Professor, UIET, Panjab University, Chandigarh, 160014, India

    Roopali Garg

Authors
  1. Preetjot Kaur
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  2. Roopali Garg
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Corresponding author

Correspondence to Preetjot Kaur .

Editor information

Editors and Affiliations

  1. Electronics and Communication Engineering, Gnanamani College of Technology, Namakkal, Tamil Nadu, India

    G. Ranganathan

  2. Department of Electrical Engineering, Dayeh University, Chang-Hwa, Taiwan

    Joy Chen

  3. University of Coimbra, Rio Tinto, Portugal

    Álvaro Rocha

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Kaur, P., Garg, R. (2020). Towards Convolution Neural Networks (CNNs): A Brief Overview of AI and Deep Learning. In: Ranganathan, G., Chen, J., Rocha, Á. (eds) Inventive Communication and Computational Technologies. Lecture Notes in Networks and Systems, vol 89. Springer, Singapore. https://doi.org/10.1007/978-981-15-0146-3_38

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  • DOI: https://doi.org/10.1007/978-981-15-0146-3_38

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-0145-6

  • Online ISBN: 978-981-15-0146-3

  • eBook Packages: EngineeringEngineering (R0)

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