AI-Driven Transformation: Digitizing of Official Moroccan Documents

This article series explores the intersection of artificial intelligence and the digitization of official Moroccan documents. Beginning with the creation of a Multilingual Character Recognition Dataset, the series progresses to unravel the challenges and solutions in character recognition using pre-trained models. It culminates in a transformative approach that combines Computer Vision and Natural Language Processing for efficient document data extraction. Beyond technical advancements, these articles highlight the identity preservation of documents and broader implications of leveraging AI for document digitization in Morocco. The experimental results demonstrate remarkable performance, with a final model achieving minimal loss (1.6622e−05) and maximum accuracy, recall, precision, and F1 score (all at 100%) during training. The validation phase further confirms the model’s robustness, achieving an accuracy of 99.46% and a corresponding recall, precision, and F1 score of 99.48%.