DeepTread: Exploring Transfer Learning in Tyre Quality Classification

In recent years, the automotive industry has witnessed a significant shift towards leveraging advanced technologies for quality control and assessment, with a particular focus on tire quality. This research study presents “DeepTread,” an innovative approach that explores the untapped potential of transfer learning in the domain of tire quality classification. Transfer learning, a powerful paradigm within deep learning, allows the adaptation of pre-trained neural networks for the purpose of tire quality evaluation. By leveraging the knowledge gained from various related domains, DeepTread aims to improve the accuracy and efficiency of tire quality classification, thereby contributing to safer and more reliable automotive solutions. The methodology's effectiveness is validated through extensive experiments, demonstrating promising results and encouraging future developments in the field of tire quality assessment.