Posts

Showing posts with the label data capture solutions

Infrrd’s AI-enabled Platform Optimizes Invoice Management

Image
Infrrd’s AI-enabled platform transforms invoice management by easing the traditional error-prone process. It holds the capability to analyze, extract, and validate data from invoices of different formats and layouts. Additionally, the platform delivers extracted data into any pre-existing tool.  Click here to know more:  https://hubs.ly/H0kyVvd0

To Know About Building An OCR Scanner From Scratch

Image
Optical Character Recognition (OCR) tools have come a long way since their introduction in the early 1990s. The ability of OCR software to convert different types of documents such as PDFs, files or images into editable and easily storable format has made corporate tasks effortless. Not only this, it’s ability to decipher a variety of languages and symbols gives Infrrd OCR Scanner an edge over ordinary scanners. However, building a technology like this isn’t a cakewalk. It requires an understanding of machine learning and computer vision algorithms. The main challenge one can face is identifying each character and word. So in order to tackle this problem we’re listing some of the steps through which building an OCR scanner will become much more clearer. Here we go: 1. START WITH OPTICAL SCANNING:   Consider the idea of putting together a good optical scanner, to begin with. With a scanner, one can capture an image of the original file or document. Remember to select an opt...

Peeking into Graph Extraction using Infrrd’s IDC Platform

Image
Whether you’re presenting an annual report, comparing sales figures, or highlighting a trend, visual representations such as graphs or charts are a great help to understand data elements quickly. However, in today’s hyper-interactive world, it’s hard to understand why data still continues to be represented as colorful graphs. These data trapped visual representations that cause restrictions in harnessing the data or make better decisions. With an increase in document volumes and a growing number of layouts, graph extraction has become a complex process; its optimization is a struggle for many organizations. Manual data retyping is prone to up 90% error, is time-consuming, and is therefore not scalable. This grinding process also requires significant rework and is an area that could benefit from   AI-enabled automated platforms . Many enterprises already understood this and are ready to jump right into automated solutions, implement them into their business processes, and reap...

What is the best OCR extraction method on printed text?

Image
I spotted another interesting question on Quora related to  machine learning & OCR , here’s my answer: I will give you a consultant’s answer – you may not like it but here goes – “It depends”. The ‘best’  OCR extraction  method depends on the context of what you are trying to extract. My guess is that you are not talking about the OCR process itself. But, rather how to extract features out of the text that OCR spits out. ​There are two broad approaches for extraction depending on whether you know the kind of data you are dealing with (invoices, tax docs, grocery labels, etc) or you do not: DOMAIN-BASED OCR EXTRACTION This approach helps when you know beforehand the kind of data extraction you are after. Let’s say you were trying to extract features of wines from a set of wine ratings and notes that you have OCR-ed. Before you can do the feature extraction, you may consider running topic modeling algorithms on a large collection of existing wine notes to fig...

Here is How Infrrd OCR Tool Is Making A Difference

Image
When introduced,  Optical Character Recognition software  was considered to be a boon for businesses. Instead of manually transferring data from records, one could now simply extract data from them. Later they can enter it automatically into in-house systems. We can save hours of manual labor but there remains a caveat. Errors introduced during the extraction process remain in your system. Before we recognize and fix the errors it can stall the work for many hours. OCR scanners are prone to fail when one tries to extract data from old documents. Either the fading of the print or the lack of contrast can lead the software to incorrect recognition of patterns. Additionally, most online  OCR software  is designed to work with English as a language. But not everybody uses English as their first language. If you travel to Europe, the script remains the same but the language differs. A smart engine OCR should be able to pick up this difference in language and adapt its...

Conversation with a Canvas - What makes Infrrd Intelligent Data Capture (IDC) better than OCR?

Image
Intelligent Data Capture  Infrrd’s current wave of technologies has tested a multilayered extraction model successfully that employs a suite of advanced  AI-technologies  to streamline the operational process. Infrrd’s  Intelligent Data Capture (IDC)  implementation can help and make a significant impact on operations and workflows with near-perfect accuracy. It’s prolific and definitely the next big thing that’s gaining major traction in the enterprise environment. But this is just a tip of the iceberg. Adapting IDC provides a single point of access for all of your business information. Despite numerous advantages, decision makers still think twice about why should one invest in IDC? If you’re one among them  contact us  for a  free demo  today and get your questions answered about IDC or business-specific applications. Originally published at  infrrd.ai