NLP analyzes text written in natural language, e.g. news, letters, contracts, social media posts, and so on. It can extract named entities (see NERNER is a subfield of NLP. It deals with extracted named entities, which are categorized objects in natural language, like... ), sentiment, roles, relationships, themes, and more from raw unstructured text. OCRWe speak about this a lot here. OCR is a technology used to interpret the pixels in an image as... is required before it can be applied to scanned images.
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The future of forms processing
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Is AI in Data Capture real? or: Are templates really a bad thing?
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How Language Detection can help your document automation process
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Feb
Hyperscience takes another step from ICR towards enterprise automation
In a recent press release, Hyperscience, a company originally known for its ICRICR is an...
Feb
Finding the best OCR engine for you
OCR use cases and flavors Before we dive into the details, let me explain what...
Jan
How to make the job of an OCR engine really difficult
Our new AP Automation software My accounting department bought a new software for AP AutomationAP...
Jan
OCR and ICR – an overview
OCR, ICR, cursive handwriting, machine print... See how OCR technology recognizes these writing styles and...
Dec
Named Entity Extraction – How does it solve real business problems?
What is Named Entity Recognition? Named Entity Extraction (NERNER is a subfield of NLP. It...
Dec