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Pixel and Embedding Consistency Loss for License Plate Super-Resolution

A training objective for image super-resolution that augments the standard pixel-wise reconstruction loss with an embedding-similarity term. A Siamese network encodes the super-resolved image and its high-resolution target, and a contrastive loss forces their embeddings to agree, so the network optimizes perceptual and semantic fidelity rather than pixel accuracy alone. Applied to license-plate images, it improves both image-quality metrics and downstream optical-character-recognition accuracy.