pytorch

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  PyTorch CRNN: Seq2Seq Digits Recognition w/ CTC

  This article discusses handwritten character recognition (OCR) in images using sequence-to-sequence (seq2seq) mapping performed by a Convolutional Recurrent Neural Network (CRNN) trained with Connectionist Temporal Classification (CTC) loss. The aforementioned approach is employed in multiple modern OCR engines for handwritten...

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  Improving Tesseract 4's OCR Accuracy through Image Preprocessing

  In this work I took a look at Tesseract 4’s performance at recognizing characters from a challenging dataset and proposed a minimalistic convolution-based approach for input image preprocessing that can boost the character-level accuracy from 13.4% to 61.6% (+359% relative...

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  PyTorch Iterative FGVM: Targeted Adversarial Samples for Traffic-Sign Recognition

  Inspired by the progress of driverless cars and by the fact that this subject is not thoroughly discussed I decided to give it a shot at creating smooth targeted adversarial samples that are interpreted as legit traffic signs with a...

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