Feb 6, 2019 · An Evaluation of OCR Systems Against Adversarial Machine Learning. Conference paper; First Online: 06 February 2019. pp 126–141; Cite this ...
This approach uses adversarial machine learning techniques, based on crafting inputs in an evolutionary manner, in order to adapt documents by performing a ...
This approach uses adversarial machine learning techniques, based on crafting inputs in an evolutionary manner, in order to adapt documents by performing a ...
List of references · Smith, R.: An overview of the Tesseract OCR engine. · Mori, S., Suen, C.Y., Yamamoto, K.: Historical review of OCR research and development.
The findings suggest that adversarial attacks can conduct a more substantial influence on OCR models through perturbations that are even less perceptible.
An evaluation of OCR systems against adversarial machine learning. D Sporici, M Chiroiu, D Ciocîrlan. Innovative Security Solutions for Information Technology ...
OCR post-correction for detecting adversarial text images
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Optical character recognition (OCR) systems have been used to detect images with malicious content, where the embedded text gets extracted and classified using ...
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Feb 8, 2020 · The adop- tion of deep neural network (DNN) in OCR results in the vulnerability against adversarial examples which are crafted to mislead the ...
Sep 7, 2019 · In this article, I'm going to discuss about my Bachelor's degree final project, which is about evaluating the robustness of OCR systems ...
We evaluate the effects of colored watermarks and other languages under real-world application settings. Last, we propose a positive application of the FAWA, ...