ADAS / IRAN ROAD SIGNS
Iranian Traffic Sign Recognition
A TSR case for SAIRAN: Iranian road-sign recognition under scarce data, low light, damage, and noisy conditions
When the sign is small, the cost of error is large
The TSR case is designed around real road frames, occluded signs, damaged panels, and low-light conditions. The page mirrors that mission with road rhythm, scan lines, and the actual project video
Data domain
Local signs and real road conditions
Use case
Driver assistance and smart mobility
Focus
Night, rain, snow, dust, and damaged signs
Project story
From limited data to a dependable perception layer for real roads
This case targets one of the hardest perception layers in intelligent driving: a small sign, sometimes damaged or partially hidden, inside frames disturbed by light, rain, dust, and vehicle motion. The technical path covered problem framing, architecture, training, evaluation, and deployment readiness. Augmentation strategies addressed scarce labelled data, while CNN and attention mechanisms improved robustness for Iranian road signs
Computer VisionCNNAttentionData AugmentationADASPython
Road perception dashboard
Recognition architecture
A TSR pipeline combining CNN features and attention mechanisms to catch small, noisy road signals
Data strategy
Augmentation plans for scarce labelled data and harsh environmental scenarios
Deployment readiness
Technical consulting from problem framing to training, evaluation, and ADAS readiness
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