Machine Learning & Uses in OCR

Machine learning is a kind of Artificial Intelligence (AI) that uses algorithms trained to make predictions and classifications to achieve accurate results. It imitates human intelligence and predicts possible output values based on historical data. 

An example application of machine learning is personalizing customers’ feeds depending on their interests and past transactions. Machine learning is also used in OCR to make the conversion of documents more efficient and accurate. The important aspect of machine learning is that it is capable of applying corrected errors to future processing thus imrocong its oerfirmance over time.

Since OCR is a technology used for converting any kind of image containing written text into machine-readable text, machine learning is incorporated into the system to compare image features and way of writing with a database, then pick the character’s closest match. 

Through the years, the use of machine learning continues to improve the accuracy of OCR in processing documents.  OCR integrated with machine learning can identify text in any type of data, allowing for comprehensive and reliable identification and text transformation. 

There are several very many applications where OCR with machine learning is needed, such as receipt scanning, traffic sign recognition, ID validation, data exraction from forms and license plate recognition. Moreover, Ssince text recognition using machine learning provides greater accuracy than the earlier versions of OCR, this allows business owners to create OCR solutions to address a wider range of challenges.