Auto-ML Deep Learning for Rashi Scripts OCR

@article{Mahpod2018AutoMLDL,
  title={Auto-ML Deep Learning for Rashi Scripts OCR},
  author={Shahar Mahpod and Yosi Keller},
  journal={ArXiv},
  year={2018},
  volume={abs/1811.01290}
}
In this work we propose an OCR scheme for manuscripts printed in Rashi font that is an ancient Hebrew font and corresponding dialect used in religious Jewish literature, for more than 600 years. The proposed scheme utilizes a convolution neural network (CNN) for visual inference and Long-Short Term Memory (LSTM) to learn the Rashi scripts dialect. In particular, we derive an AutoML scheme to optimize the CNN architecture, and a book-specific CNN training to improve the OCR accuracy. The… CONTINUE READING
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References

Publications referenced by this paper.
SHOWING 1-10 OF 34 REFERENCES

Robust Recognition of Degraded Documents Using Character N-Grams

  • 2012 10th IAPR International Workshop on Document Analysis Systems
  • 2012
VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL

Compression Fractures Detection on CT

  • Medical Imaging: Computer-Aided Diagnosis
  • 2017
VIEW 2 EXCERPTS

Kannada handwritten word conversion to electronic textual format using HMM model

  • 2016 International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)
  • 2016
VIEW 2 EXCERPTS

Multilingual OCR for Indic Scripts

  • 2016 12th IAPR Workshop on Document Analysis Systems (DAS)
  • 2016
VIEW 1 EXCERPT

Recognition of Offline Handwritten Chinese Characters Using the Tesseract Open Source OCR Engine

  • 2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)
  • 2016
VIEW 2 EXCERPTS

Robust Scene Text Recognition with Automatic Rectification

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2016
VIEW 1 EXCERPT