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CNN: A Fundamental Unit of New Age AI
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Author(s): Mohan Kumar Dehury (Amity University, India), Ronit Kumar Gupta (Amity University, India)and Tannisha Kundu (Amity University, India)
Copyright: 2024
Pages: 34
Source title:
Digital Technologies in Modeling and Management: Insights in Education and Industry
Source Author(s)/Editor(s): G. S. Prakasha (Christ University, India), Maria Lapina (North-Caucasus Federal University, Russia), Deepanraj Balakrishnan (Prince Mohammad Bin Fahd University, Saudi Arabia)and Mohammad Sajid (Aligarh Muslim University, India)
DOI: 10.4018/978-1-6684-9576-6.ch003
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Abstract
The field of artificial intelligence (AI) is very promising with the emergence of machine learning and deep learning algorithms. The rise of convolutional neural networks (CNN) is very propitious in deep learning as it is more accurate and powerful than previously known soft computational models like artificial neural networks (ANN) and recurrent neural networks (RNN). CNN is ANN with steroids. These soft computational models are inspired by biological models that give an approximate solution to image-driven pattern recognition problems. The near perfect precision of CNN models offers a better way to recognize patterns and solve real-world problems and provide approximate solutions which are near precision. These technologies have enhanced the trust with humans. Its results have been accepted widely. This chapter aims to provide brief information about CNNs by introducing and discussing recent papers published on this topic and the methods employed by them to recognize patterns. This chapter also aims to provide information regarding dos and don'ts while using different CNN models.
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