Xiang-Yang Li

Towards Efficient and Explainable Road Crack Detection: A Transfer Learning-Driven SqueezeNet-based Approach

This study proposes an efficient and interpretable crack detection method that integrates SqueezeNet with transfer learning that achieves high detection performane, specifically, accuracy (ACC), true positive rate (TPR), true negative rate (TNR), positive predictive value (PPV), and F1-score (F1) all exceed 91%.