Introduction
In the light of the increasing popularization in OCR in conjunction with AI Machine Learning, more and more business executives are seeking ways to boost their businesses with this deadly combination.
If you're one of those, continue reading to discover more about OCR and how OCR is made possible through machine learning and what it could do to provide businesses with advantages, and more.
The Impact of AI on OCR
The optical character recognition (OCR) techniques are currently being transformed through artificial intelligence. OCR is a kind of computer vision which scans text images and converts these into machine-readable forms. In other words it converts written or typed text in physical documents into digital versions.
Many business owners during the 1990s utilized OCR Datasets or text recognition, to convert physically stored data in to digital. Since then, OCR technology has advanced in its quality, but the demand for greater accessibility has increased. OCR's value has been boosted due to recent AI break throughs that have increased accuracy and speed. Artificial intelligence means that human monitoring is not required at any time.
Business Benefit From OCR & Artificial Intelligence
Easy Digitalization
Prior to OCR conversion of physical text into digital was a lengthy and error-prone procedure. This means that the conversion is quicker using OCR Training Dataset which is also more exact in relation to the original text. Viewers can edit, arrange and search for documents after OCR transforms the data into digital. They can also send it to email addresses or embed it on websites, and keep it compressed documents. This obviously minimizes the requirement for storage space, leading to savings for businesses who rely on a lot of documents, like law firms, mortgage companies, or even mortgage companies.
More Accurate Results
By combining OCR as well as AI as well as machine-learning (ML) teams are able to convert text more precisely and identify any issues that might arise during the process of conversion. AI can also be more able to comprehend handwriting, enabling digitization of a greater number of documents. Because of the distinct particularities of each individual human handwriting, handwriting remains a major challenge for AI but, as it accumulates more handwriting-related training Dataset For Machine Learning, computers are getting better at this field as well.
No Supervisors Needed
For an example of AI-powered OCR Technology how this kind of technology could digitally scan print invoices. Let's suppose that the scanner mistook the total amount of the invoice as $800, when in fact it was $8,000. Prior to AI then, it was likely that the OCR program would not notice the error and must be discovered by a human review. But, with AI technology an algorithm is able to review every document in the file, calculate that the subtotals for the services performed should total $8,000, and then correct the error without necessity of human intervention.
Effective & Efficient
Businesses can review a vast amount of documents without incurring expenses for staff by using this feature for understanding documents. The reduction of administrative work could help improve the employee's engagement and reduce turnover. As AI-powered OCR improves efficiency and becomes affordable, experts expect that demand for OCR to grow.
Use Case of Optical Character Recognition (OCR)
Data Classifications
Utilizing OCR postal offices are able to sort mail and banks can electronically deposit checks. OCR is also utilized to sort data.
Data Processing
The most popular use cases for OCR can be data entry. It lets companies make physical copies documents for business and legal purposes into PDF files so that employees are able to edit and style and search exactly like they would with the word processor.
Others
With OCR software, search engines are able to search for printouts, upload authentic legal document to database, as well as convert documents to text for people who are visually impaired. In addition to translation applications as well as online text databases like Google Books, and security cameras that detect license plates. OCR can be found in a variety of applications.
Use Cases of OCR in Various Industries
But, as companies gradually move to digital platforms, OCR technology is expected to become a requirement for businesses. In this article we'll look at OCR Utilization Cases in seven different industries.
- Communication
- Legal
- Insurance
- Banking
- Tourism
- Healthcare
- Retail & eCommerce
Conclusion
Global Technology Solutions (GTS) OCR has got your business covered. With its remarkable accuracy of more than 90% and fast real-time results, GTS helps businesses automate their data extraction processes. In mere seconds, the banking industry, e-commerce, digital payment services, Image Data Collection, AI Training Dataset, Video Dataset and many more can pull out the user information from any type of document by taking advantage of OCR technology. This reduces the overhead of manual data entry and time taking tasks of data collection.
