The research deals with deep learning-based, voice-operated traffic sign recognition to improve road safety. A deep learning-based model is presented for the recognition of traffic signs with CNN, trained on GTSRB Dataset with an identification and categorization precision of 95%. The developed system detects signs and, through audio warnings by speakers, assists drivers to make quick decisions. The system aims to mitigate accidents caused by missed or misinterpreted signage by alerting drivers to nearby traffic signs and rules. This approach has potential applications in both driver assistance systems and autonomous vehicles.
Road Safety with Deep Learning Voice Based Traffic Sign
28.03.2025
433446 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Deep Learning Approach to Classify Road Traffic Sign Images
Springer Verlag | 2021
|VIRTUALIZED ROAD TRAFFIC SIGN GENERATION FOR ENHANCING ROAD SAFETY
Europäisches Patentamt | 2022
|VIRTUALIZED ROAD TRAFFIC SIGN GENERATION FOR ENHANCING ROAD SAFETY
Europäisches Patentamt | 2022
|Traffic Sign Classification for Road Safety using CNN
IEEE | 2024
|