Moroccan licence plate detection and recognition using a YOLOv10s detector and a dual-CNN module

Key Points

• To enhance the accuracy of license plate detection and recognition in Morocco using advanced neural network techniques.
• Utilized a YOLOv10s detector for object detection and identification of license plates.
• Implemented a dual-CNN module to improve image processing and recognition accuracy.
• Tested the system on a dataset of Moroccan license plates to evaluate performance.
• Achieved a recognition accuracy of over 90% for Moroccan license plates.
• Demonstrated a significant reduction in processing time compared to previous models.
• Showed improved performance metrics, indicating better detection rates across various conditions.