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Infrrd Cited in Two Recent Gartner Hype Cycle Reports

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  400 U.S.-based Companies Processing More than One Million Invoices Annually Cite Dramatic Increase in IDP Adoption for Accounts Payable FunctionCompany Recognized as Sample Vendor for Intelligent Document Processing SAN JOSE, Calif. … August 23, 2022 …  Infrrd , a leading provider of Intelligent Document Processing (IDP) solutions, announced today it was named a Sample Vendor for IDP in two recent  Gartner  Hype Cycle reports. Both reports cite the role of IDP in business process improvement. The first report,  Hype Cycle for Natural Language Technologies, 2022 , published on July 11, 2022, discusses how advances in artificial intelligence and (AI) and machine learning (ML) are driving innovation and fostering advances in natural language technologies (NLT)and designates where these new opportunities and methods can prove most beneficial. The report states that, “ IDP uses natural language technologies and computer vision to extract data from structured and un...
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Uncovering the Data Extraction Challenge of Annual Reports

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Data Extraction From Annual Reports Do you spend a lot of time daily in extracting meaningful insights from  𝐜𝐨𝐦𝐩𝐥𝐞𝐱 𝐚𝐧𝐧𝐮𝐚𝐥 𝐫𝐞𝐩𝐨𝐫𝐭𝐬 ? Annual reports come in all sorts of formats with non-standard taxonomy being the norm more than the exception. Add in that important information is always presented in tables, charts, graphs, and other containers  OCR   has difficulty reading, and the picture is clear.A single Annual Report can be up to 186 pages or more. When humans are left to manually extract critical data from each page, how long do you think a single review of a single document would take? Now what if you had hundreds? Thousands to review? Find out how  𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭 𝐃𝐚𝐭𝐚 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠  platform will make your time more beneficial READ MORE
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How to Prepare Data For OCR Learning

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Data analysis without data preparation it is a myth. Unless we feed the right data in a proper format, Machine Learning algorithms won’t be able to solve our problem. If we give one wrong input then we end up where we started. So it’s very important to understand what data preparation is and how one can do it. Data, in its original form, may have a lot of missing pieces or disarrangement. Through data processing, one can modify this raw information from a specific database to a format which is understandable and learnable by the machine. Mentioned below are the ways that, we at Infrrd , employ in preparing our data. 1. Data selection: It is necessary first to identify the type of data we are going to be working with. One has to keep in mind whether the available data will be able to address an existing problem or not. We keep certain factors in consideration before selecting the data: Data should not be of low quality: Low-quality input= low-quality output. Dataset is not err...
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