Abstract
Convolutional neural network (or CNN) is a special type of multilayer neural network or deep learning architecture inspired by the visual system of living beings. The CNN is very much suitable for different fields of computer vision and natural language processing. The main focus of this chapter is an elaborate discussion of all the basic components of CNN. It also gives a general view of foundation of CNN, recent advancements of CNN and some major application areas.
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Notes
- 1.
Notable thing: CNN uses a set of multiple filters in each convolutional layers so that each filter can extract the different types of features.
- 2.
“The pooling operation used in convolutional neural networks is a big mistake and the fact that it works so well is a disaster.” –Geoffrey Hinton.
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Ghosh, A., Sufian, A., Sultana, F., Chakrabarti, A., De, D. (2020). Fundamental Concepts of Convolutional Neural Network. In: Balas, V., Kumar, R., Srivastava, R. (eds) Recent Trends and Advances in Artificial Intelligence and Internet of Things. Intelligent Systems Reference Library, vol 172. Springer, Cham. https://doi.org/10.1007/978-3-030-32644-9_36
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