BLPR achieves 89.6% character-level accuracy on real Bolivian license plates by combining synthetic pretraining, geometric rectification, and confidence-triggered VLM fallback while releasing the first public Bolivian LPDR dataset.
A robust real-time automatic license plate recognition based on the YOLO detector
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LPLCv2 is a larger, more annotated dataset for fine-grained license plate legibility classification with a baseline model reaching 89.5% F1-score via a new training method and camera-contamination protocol.
citing papers explorer
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BLPR: Robust License Plate Recognition under Viewpoint and Illumination Variations via Confidence-Driven VLM Fallback
BLPR achieves 89.6% character-level accuracy on real Bolivian license plates by combining synthetic pretraining, geometric rectification, and confidence-triggered VLM fallback while releasing the first public Bolivian LPDR dataset.
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LPLCv2: An Expanded Dataset for Fine-Grained License Plate Legibility Classification
LPLCv2 is a larger, more annotated dataset for fine-grained license plate legibility classification with a baseline model reaching 89.5% F1-score via a new training method and camera-contamination protocol.