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Convolutional Neural Network

Convolutional Neural Network

Mário Pereira Véstias
Copyright: © 2022 |Pages: 17
ISBN13: 9781668424087|ISBN10: 1668424088|EISBN13: 9781668424094
DOI: 10.4018/978-1-6684-2408-7.ch077
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MLA

Véstias, Mário Pereira. "Convolutional Neural Network." Research Anthology on Artificial Neural Network Applications, edited by Information Resources Management Association, IGI Global, 2022, pp. 1559-1575. https://doi.org/10.4018/978-1-6684-2408-7.ch077

APA

Véstias, M. P. (2022). Convolutional Neural Network. In I. Management Association (Ed.), Research Anthology on Artificial Neural Network Applications (pp. 1559-1575). IGI Global. https://doi.org/10.4018/978-1-6684-2408-7.ch077

Chicago

Véstias, Mário Pereira. "Convolutional Neural Network." In Research Anthology on Artificial Neural Network Applications, edited by Information Resources Management Association, 1559-1575. Hershey, PA: IGI Global, 2022. https://doi.org/10.4018/978-1-6684-2408-7.ch077

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Abstract

Machine learning is the study of algorithms and models for computing systems to do tasks based on pattern identification and inference. When it is difficult or infeasible to develop an algorithm to do a particular task, machine learning algorithms can provide an output based on previous training data. A well-known machine learning model is deep learning. The most recent deep learning models are based on artificial neural networks (ANN). There exist several types of artificial neural networks including the feedforward neural network, the Kohonen self-organizing neural network, the recurrent neural network, the convolutional neural network, the modular neural network, among others. This article focuses on convolutional neural networks with a description of the model, the training and inference processes and its applicability. It will also give an overview of the most used CNN models and what to expect from the next generation of CNN models.

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