Challenge
An Emirati government entity aims to extract data from historical legislative documents which include handwritten Arabic text. The documents have often insufficient quality to be automatically read with traditional recognition engines.
Solution
Using docBrain custom neural networks, document image quality has improved, resulting in better readability. docBrain is currently training a new neural network model for automatic recognition of Arabic handwriting. The objective is to extract accurate quality data with fewer errors and decrease the number of manual interventions and validations.
This project illustrates that docBrain can teach itself the Arabic characters (and for that matter any type of non-Latin alphabet) if there are enough documents and data for training the neural networks.
"The one-of-its-kind docBrain platform is the missing link to create a comprehensive ecosystem that delivers end-to-end automation of document processing, operating seamlessly with RPA platforms and digital touchpoints. Being able to finally understand and analyse any type of hand written or printed Arabic documents is a real AI revolution for the region."
Thierry Petrens, CEO Kleptika