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Online shopping is on the rise as it’s convenient to shop from home and get products delivered. According to NPR, 92 percent of American consumers make purchases through ecommerce, and that number is only increasing.
When it comes to online shopping, consumers have high expectations about how their experience should be. They’re looking for quick, easy solutions to their problems from brands who care about their buying motives.
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, but 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: