automated inspection
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A Hybrid Artificial Intelligence Approach for Defect Detection in Fiber-Reinforced Composite Steels
Abstract: Defect detection in fiber-reinforced composite materials is important for maintaining product quality and ensuring structural reliability. However, manual inspection can be time-consuming and may depend on the experience of the inspector. This study presents a hybrid Convolutional Neural Network–Grey Wolf Optimization (CNN–GWO) approach for automated detection and classification of defects in fiber-reinforced composite materials. The proposed approach combines CNN-based feature learning with GWO-based hyperparameter optimization to improve the selection of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 · pp. 285–310 Read article