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ICDAR
2007
IEEE
13 years 11 months ago
Context-Sensitive Error Correction: Using Topic Models to Improve OCR
Modern optical character recognition software relies on human interaction to correct misrecognized characters. Even though the software often reliably identifies low-confidence ...
Michael L. Wick, Michael G. Ross, Erik G. Learned-...
ICDAR
2009
IEEE
13 years 11 months ago
Robust Recognition of Documents by Fusing Results of Word Clusters
The word error rate of any optical character recognition system (OCR) is usually substantially below its component or character error rate. This is especially true of Indic langua...
Venkat Rasagna, Anand Kumar 0002, C. V. Jawahar, R...
CVPR
2010
IEEE
14 years 1 months ago
Improving State-of-the-Art OCR through High-Precision Document-Specific Modeling
Optical character recognition (OCR) remains a difficult problem for noisy documents or documents not scanned at high resolution. Many current approaches rely on stored font models...
Andrew Kae, Gary Huang, Erik Learned-miller, Carl ...
ICDAR
2009
IEEE
13 years 11 months ago
Scaling Up Whole-Book Recognition
We describe the results of large-scale experiments with algorithms for unsupervised improvement of recognition of book-images using fully automatic mutual-entropy-based model adap...
Pingping Xiu, Henry S. Baird
SPIN
2009
Springer
13 years 11 months ago
Identifying Modeling Errors in Signatures by Model Checking
: Most intrusion detection systems deployed today apply misuse detection as analysis method. Misuse detection searches for attack traces in the recorded audit data using predefined...
Sebastian Schmerl, Michael Vogel, Hartmut Kön...