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Creating a Modern OCR Pipeline Using Computer Vision and Deep Learning - Dropbox

dropbox.tech · 4,996 words · saved by 1 readers

In previous posts we have described how Dropbox’s mobile document scanner works. The document scanner makes it possible to use your mobile phone to take photos and "scan" items like receipts and invoices. Our mobile document scanner only outputs an image — any text in the image is just a set of pixels as far as the computer is concerned, and can’t be copy-pasted, searched for, or any of the other things you can do with text.

Creating a Modern OCR Pipeline Using Computer Vision and Deep Learning - Dropbox --> --> --> Creating a Modern OCR Pipeline Using Computer Vision and Deep Learning // By Brad Neuberg • Apr 12, 2017 In this post we will take you behind the scenes on how we built a state-of-the-art Optical Character Recognition (OCR) pipeline for our mobile document scanner . We used computer vision and deep learning advances such as bi-directional Long Short Term Memory (LSTMs), Connectionist Temporal Classification (CTC), convolutional neural nets (CNNs), and more. In addition, we will also dive deep into

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