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Optical Character Recognition


Dark data analytics for actionable business insights

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The first generation RPA focuses mainly on structured data, where data extraction is straightforward and it usually results in just 30%-40% Straight Through Processing (STP). In an effort to bring structure to the unstructured data, enterprises turn to cognitive automation technologies, which is a convergence of RPA and AI and ML. RPA use cases are content-dependent and in cognitive automation models, the idea is to make the RPA bots learn from human behavior. For this, vision technology like optical character recognition (OCR), document extraction tools, ML or a combination of these capabilities are leveraged to bring structure to the unstructured and semi-structured data. The major challenge in automating data extraction is due to the presence of voluminous unstructured dark data.


AI needs to face up to its invisible worker problem

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Many of the most successful and widely used machine learning models are trained with the help of thousands of low-paid gig workers. Millions of people around the world earn money on platforms like Amazon Mechanical Turk, which allow companies and researchers to outsource small tasks to online crowdworkers. According to one estimate, more than a million people in the US alone earn money each month by doing work on these platforms. Around 250,000 of them earn at least three quarters of their income this way. But despite many working for some of the richest AI labs in the world, they are paid below minimum wage and given no opportunities to develop their skills.


AI-Based OCR Technology Revolutionizing the Banking Sector - ReadWrite

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The advent of technology has brought convenience to life. Believe it or not, survival without technology is one of the darkest thoughts that can cross your mind in the digital era. The world has become a global village thanks to rapid digitization, but it has also opened doors for many fraudsters to step in and terrify people. Organizations in every sector are unsafe due to increasing ransomware and data breaches. Considering the increasing number of frauds, companies opt for robust verification systems with OCR technology to only onboard legitimate customers.


Saturday mail deliveries to end in Japan as early as autumn next year

The Japan Times

A revision to the postal law was enacted Friday, allowing Japan Post Co. to scrap Saturday and next-day deliveries of ordinary mail as early as autumn next year. The bill to amend the postal law was approved at a plenary session of the House of Councilors. The move reflects a decline in mail volumes and is also aimed at improving post office personnel's work conditions. The government had delayed the submission of the bill to the Diet in order to allow the Japan Post Holdings Co. group to prioritize dealing with the issue of irregularities in sales of Kampo postal life insurance products at post offices. The revised law will reduce the frequency of general mail deliveries from at least six days a week to at least five days a week.


Vietnam launches akaBot platform to digitally transform businesses

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The Ministry of Information and Communications (MIC) launched the akaBot platform – corporate process automation – in Hanoi, earlier this week. A press release said that the technology, akaBot is the FPT's third make-in-Vietnam platform. It is among 33 other platforms selected by MIC to introduce and sponsor media in the "Friday of Technology" programme, to serve the National Digital Transformation Programme to 2025, with the vision to 2030, which was approved by the Prime Minister in June. According to the development team, akaBot is a robotic process automation (RPA) solution for businesses with "virtual assistants" capable of simulating human manipulation, helping perform repetitive tasks in large numbers. With the core technology of RPA, akaBot is capable of integrating artificial intelligence (AI) and optical character recognition (OCR) technology to build comprehensive, non-invasive intelligent automation solutions, which can interact with all business software such as Word and Excel.


Applying Machine Learning to Recognize Handwritten Characters

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Handwritten character recognition is a field of research in artificial intelligence, computer vision, and pattern recognition. A computer performing handwriting recognition is said to be able to acquire and detect characters in paper documents, pictures, touch-screen devices and other sources and convert them into machine-encoded form. Its application is found in optical character recognition, transcription of handwritten documents into digital documents and more advanced intelligent character recognition systems. Handwritten character recognition can be thought of as a subset of the image recognition problem. Basically, the algorithm takes an image (image of a handwritten digit) as an input and outputs the likelihood that the image belongs to different classes (the machine-encoded digits, 1–9).


Computer Vision: Python OCR & Object Detection Quick Starter

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Online Courses Udemy - Computer Vision: Python OCR & Object Detection Quick Starter, Quick Starter for Optical Character Recognition, Image Recognition Object Detection and Object Recognition using Python Hot & New Created by Abhilash Nelson English Students also bought Python 3.8 for beginners 2020 Docker for Beginners Python Programming from Basics to Advanced FL Studio 20 - EDM Masterclass Music Production in FL Studio Microsoft Azure Data Lake Storage Service (Gen1 & Gen2) Geospatial Data Analyses & Remote Sensing: 4 Classes in 1 Preview this course GET COUPON CODE Description Hi There! welcome to my new course'Optical Character Recognition and Object Recognition Quick Start with Python'. This is the third course from my Computer Vision series. Image Recognition, Object Detection, Object Recognition and also Optical Character Recognition are among the most used applications of Computer Vision. Using these techniques, the computer will be able to recognize and classify either the whole image, or multiple objects inside a single image predicting the class of the objects with the percentage accuracy score. Using OCR, it can also recognize and convert text in the images to machine readable format like text or a document.


KuroNet: Regularized Residual U-Nets for End-to-End Kuzushiji Character Recognition

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Kuzushiji, a cursive writing style, had been used in Japan for over a thousand years starting from the eighth century. Over 3 million books on a diverse array of topics, such as literature, science, mathematics and even cooking are preserved. However, following a change to the Japanese writing system in 1900, Kuzushiji has not been included in regular school curricula. Therefore, most Japanese natives nowadays cannot read books written or printed just 150 years ago. Museums and libraries have invested a great deal of effort into creating digital copies of these historical documents as a safeguard against fires, earthquakes and tsunamis.


How OCR Is Changing Family History • FamilySearch

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If this article caught your eye, you probably have an interest in indexing or in online historical records. Maybe you've made indexing a part of your weekly or monthly volunteer efforts. If so, keep up the amazing work! You're making it possible for people around the world to discover their ancestors and learn more about their family histories. Still, our indexing volunteers have a colossal task in front of them.


zomato digitizes menus using Amazon Textract and Amazon SageMaker

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This post is co-written by Chiranjeev Ghai, ML Engineer at zomato. zomato is a global food-tech company based in India. Are you the kind of person who has very specific cravings? Maybe when the mood hits, you don’t want just any kind of Indian food—you want Chicken Chettinad with a side of paratha, and nothing […]