Optimal Design of Convolutional Neural Network Architectures Using Teaching–Learning-Based Optimization for Image Classification

Optimal Design of Convolutional Neural Network Architectures Using Teaching–Learning-Based Optimization for Image Classification

Convolutional neural networks (CNNs) have exhibited significant performance gains over conventional machine learning techniques in solving various real-life problems in computational intelligence fields, such as image classification. However, most existing CNN architectures were handcrafted from scr...

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Bibliographic Details
Main Authors: Koon Meng Ang, El-Sayed M. El-kenawy, Abdelaziz A. Abdelhamid, Abdelhameed Ibrahim, Amal H. Alharbi, Doaa Sami Khafaga, Sew Sun Tiang, Wei Hong Lim
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Symmetry
Subjects:
convolutional neural networks
deep learning
image classification
optimal design of network architecture
teaching–learning-based optimization
Online Access:https://www.mdpi.com/2073-8994/14/11/2323

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https://www.mdpi.com/2073-8994/14/11/2323

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