A Hybrid Cracked Tiers Detection System Based on Adaptive Correlation Features Selection and Deep Belief Neural Networks

A Hybrid Cracked Tiers Detection System Based on Adaptive Correlation Features Selection and Deep Belief Neural Networks

Tire defects are crucial for safe driving. Specialized experts or expensive tools such as stereo depth cameras and depth gages are usually used to investigate these defects. In image processing, feature extraction, reduction, and classification are presented as three challenging and symmetric ways t...

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Bibliographic Details
Main Authors: Ali Mohsin Al-juboori, Ali Hakem Alsaeedi, Riyadh Rahef Nuiaa, Zaid Abdi Alkareem Alyasseri, Nor Samsiah Sani, Suha Mohammed Hadi, Husam Jasim Mohammed, Bashaer Abbuod Musawi, Maifuza Mohd Amin
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Symmetry
Subjects:
safe driving
tire defect detection
deep belief neural networks
feature extraction
feature selection
Online Access:https://www.mdpi.com/2073-8994/15/2/358

Internet

https://www.mdpi.com/2073-8994/15/2/358

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