Everything You Need to Know About Building an OCR Scanner from Scratch

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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:


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Lack of Workplace Training Puts AI Revolution at Risk

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I’ve written a number of times about the need to significantly expand our efforts to educate the workforce if we’re to take advantage of the latest technologies entering the market. Consulting firm Accenture has been fervent cheerleaders of this, and have banged the drum again in a recently published paper.

They argue that unless we take a radically new approach to learning, the skills gap will result in as much as $11.5 trillion in GDP growth being lost over the next ten years.


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Top 10 Most Popular AI Models

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While Artificial Intelligence and Machine Learning provide ample possibilities for businesses to improve their operations and maximize their revenues, there is no such thing as a “free lunch.”

The “no free lunch” problem is the AI/ML industry adaptation of the age-old “no one-size-fits-all” problem. The array of problems the businesses face is huge, and the variety of ML models used to solve these problems is quite wide, as some algorithms are better at dealing with certain types of problems than the others. Thus said, one needs a clear understanding of what every type of ML models is good for, and today we list 10 most popular AI algorithms:


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The Many Features of Apache MXNet GluonCV

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In preparation for my talk at the Philadelphia Open Source Conference, Apache Deep Learning 201, I wanted to have some good images for running various Apache MXNet Deep Learning Algorithms for Computer Vision. 

Using Apache open source tools – Apache NiFi 1.8 and Apache MXNet 1.3 with GluonCV I can easily ingest live traffic camera images and run Object Detection, Semantic Segmentation and Instance Segmentation.


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Sloppy QA and How to Shorten the QA Process

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Our CEO recently gave an interview with the news website PC. Check out what he had to say:

Code Issues as a Result of Making the Wrong Tests: This AI Can Help

Eli Lopian, Typemock’s CEO, was very frustrated by the lengthy time it took to develop software due to issues with testing. Therefore, he found a solution together with a few other people and as a result founded his own company.


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Machine Learning and Artificial Intelligence

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Machine Learning and Artificial Intelligence

The difference between Machine Learning and Artificial Intelligence: "Okay Google! What’s Up? Could you play my favorite track or Book a Cab from Palace Road to MG Road."

"Alexa, What time it is?" "Wake me up at 5 am." "Could you please tell me my tomorrow meetings?"


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AI and Its Discriminating Algorithms

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Artificial Intelligence has taken the industry by storm. It is spreading gems of highly advanced technological traces and with its simple touch, transforming the face of the tech world. As it paves its way into capturing diverse industries, it influences the latest trends and stirring complexities that eventually puts immense pressure on marketers, developers, and creative artists.

However, due to some shocking updates about AI algorithms that have surfaced the industry, many conflicting opinions and judgments spurred among the tech giants. The algorithms of Artificial Intelligence are reportedly being noticed to create racist and biased discrimination.


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Know How AI Helps Transform Your Software Delivery and Testing Practices

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Software Testing and Quality Assurance is like a wakeup call in the Software Development Lifecycle. It keeps nudging over intervals and enhances the software delivery process. Software Testing and the QA scene has been transforming over the last decade, especially with practices such as Agile, Shift-left, and DevOps. Artificial Intelligence (AI) has added another spin to this game, focusing on speed, accuracy, and efficiency. Can AI transform software delivery and testing? That’s a doubt that has been clarified very well. Let’s look at ways in which AI can change the game for software delivery and testing.

AI can bring in value for the development teams with shift-left practices that enable the software development process. While AI might do the needful, it is important to ensure that the practices followed for delivery and testing are effective and are able to leverage the power of AI. Hence, it is very much essential to embed trust in the processes and ensure that there is effective validation and verification.


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How Conversational AI Increases Your Competitive Edge

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In the second part of our series, Getting Started in Conversational AI, we take a look at some of the business benefits that conversational Artificial Intelligence delivers.

From speech-enabled interfaces that improve customer experience, to intelligent chatbots that deliver 24/7 customer service, or humanlike digital assistants that drive online sales revenue, conversational AI is rapidly changing customer interaction.


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Cognitive Services: Convert Text to Speech in Multiple Languages Using Asp.Net Core and C#

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In this article, we are going to learn how to convert text to speech in multiple languages using one of the important Cognitive Services APIs called Microsoft Text to Speech Service API (one of the APIs in Speech API). The Text to Speech (TTS) API of the Speech service converts input text into natural-sounding speech (also called speech synthesis). It supports text in multiple languages and gender based voice(male or female)

You can also refer the following articles on Cognitive Service.


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