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A New Method of Interval Type-2 Fuzzy-Based CNN for Image Classification

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Book cover Computational Vision and Bio-Inspired Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1318))

Abstract

Last two decades, neural networks and fuzzy logic have been successfully implemented in intelligent systems. The fuzzy neural network system framework infers the union of fuzzy logic and neural system framework thoughts, which consolidates the advantages of fuzzy logic and neural network system framework. This FNN is applied in many scientific and engineering areas. Wherever there is an uncertainty associated with data fuzzy logic place a vital rule, and the fuzzy set can represent and handle uncertain information effectively. The main objective of the FNN system is to achieve a high level of accuracy by including the fuzzy logic in either neural network structure, activation function, or learning algorithms. In computer vision and intelligent systems such as convolutional neural network has more popular architectures, and their performance is excellent in many applications. In this article, fuzzy-based CNN image classification methods are analyzed, and also interval type-2 fuzzy-based CNN is proposed. From the experiment, it is identified that the proposed method performance is well.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Karpagam College of Engineering, Coimbatore, Tamil Nadu, India

    P. Murugeswari

  2. Department of Computer Applications, NMS S. Vellaichamy Nadar College, Madurai, Tamil Nadu, India

    S. Vijayalakshmi

Authors
  1. P. Murugeswari
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  2. S. Vijayalakshmi
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, RVS Technical Campus, Coimbatore, Tamil Nadu, India

    S. Smys

  2. Departamento de Engenharia Mecanica, SDI, Faculty of Engineering, Universidade do Porto, Porto, Portugal

    João Manuel R. S. Tavares

  3. Czech Technical University in Prague, Prague, Czech Republic

    Robert Bestak

  4. College of Graduate Studies, University of Central Florida, Orlando, FL, USA

    Fuqian Shi

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Murugeswari, P., Vijayalakshmi, S. (2021). A New Method of Interval Type-2 Fuzzy-Based CNN for Image Classification. In: Smys, S., Tavares, J.M.R.S., Bestak, R., Shi, F. (eds) Computational Vision and Bio-Inspired Computing. Advances in Intelligent Systems and Computing, vol 1318. Springer, Singapore. https://doi.org/10.1007/978-981-33-6862-0_57

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