Design of a Convolutional Neural Network with Type-2 Fuzzy-Based Pooling for Vehicle Recognition

Cheng-Jian Lin (), Bing-Hong Chen, Chun-Hui Lin and Jyun-Yu Jhang
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Cheng-Jian Lin: Ph.D. Program, Prospective Technology of Electrical Engineering and Computer Science, National Chin-Yi University of Technology, Taichung 411, Taiwan
Bing-Hong Chen: Ph.D. Program, Prospective Technology of Electrical Engineering and Computer Science, National Chin-Yi University of Technology, Taichung 411, Taiwan
Chun-Hui Lin: Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung 411, Taiwan
Jyun-Yu Jhang: Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, Taichung 404, Taiwan

Mathematics, 2024, vol. 12, issue 24, 1-17

Abstract: Convolutional neural networks typically employ convolutional layers for feature extraction and pooling layers for dimensionality reduction. However, conventional pooling methods often lead to a loss of critical feature information, particularly in images with diverse content, such as vehicle images. This study proposes a novel approach to address these problems: a convolutional neural network with type-2 fuzzy-based pooling (CNN-T2FP). This innovative pooling method utilizes type-2 fuzzy membership functions to effectively manage local imprecision in feature maps. Compared with type-1 fuzzy pooling, which only addresses uncertainty to a certain extent, type-2 fuzzy pooling exhibits improved adaptability to different image contents. The experimental results of this study revealed that the CNN-T2FP achieved average accuracies of 92.14% and 93.34% on two datasets, surpassing the performance of existing pooling techniques. In addition, t-distributed stochastic neighbor embedding plots and feature visualization maps further highlighted the potential of type-2 fuzzy-based pooling to overcome the limitations of conventional pooling methods and enhance the performance of convolutional neural networks in image analysis tasks.

Keywords: vehicle recognition; type-2 fuzzy set; convolutional neural network; pooling operation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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