Optical Character Recognition (OCR) is a method for recognizing and reading text in images with Computer Vision technology. OCR enables translating printed or written text into machine-readable form so that the content can be edited and searched in. Optical character recognition is indispensable for business digitization when data from lots of paper carriers has to be transferred into a digital database.
OCR has its limitations. Firstly, it’s not always accurate. Secondly, it’s not trained to extract particular fields and analyze document structure, which is why using it to extract certain fields from documents of different layouts is challenging. OCR is unable to tell the difference between sender and recipient, payer and buyer, personal tax id and company registration number.
It is possible to build a solution using OCR outputs, but each new document layout, each new case needs to be handled programmatically, and requires human supervision, i.e. time and money.
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Computer Vision (CV)
Computer vision (CV) is a type of artificial intelligence that uses deep learning to analyze visual data for its further application.
Natural Language Processing (NLP)
Natural Language Processing (NLP) is a branch of computer science that enables machines to interpret and comprehend human language for various tasks.
Data extraction using AI refers to the automatic identification and extraction of relevant information from unstructured or semi-structured data sources, such as text documents or images.