ENHANCING TRAFFIC SIGN RECOGNITION WITH EXPLAINABLE AI: INTERPRETABLE CNN MODELS FOR IMPROVED SAFETY
Abstract
The escalating use of Convolutional Neural Network (CNN) models in traffic sign recognition promises substantial advancements in road safety. However, the lack of interpretability in these models poses challenges to understanding their decision-making processes. This research project, titled "Enhancing Traffic Sign Recognition with Explainable AI: Interpretable CNN Models for Improved Safety" addresses this issue by enhancing the interpretability of CNN models, contributing to overall road safety.
Driving, seemingly simple, demands constant alertness to surroundings. Crucial to safe driving is the interpretation of traffic signs, which convey vital information about road conditions and speed limits. In unfamiliar areas, the abundance of signs can be overwhelming, emphasizing the importance of the Traffic Sign Recognition (TSR) System.
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