<commit_before>
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%  $Description: Sample bibliography$ 
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%  $Author: scottl $ 
%  $Date: 2006-12-19 21:29:44 $
%  $Revision: 1.1 $
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@Article{ex1,
   author =   "Author, <NAME>",
   title =   "Some Related Article {I} Wrote", 
   journal =   "Some Fine Journal",
   month = "January",
   number = "7",
   year =   "1999",
   volume =   "99",
   pages =   "1-100",
}


@Book{ex2,
   author =   "Expert, <NAME>", 
   title =   "A Book He Wrote", 
   publisher =   "His Publisher",
   address = "Erewhon, NC",
   year =   "1999"
}
<commit_msg>added most of the required papers to the bibliography.<commit_after>%% This BibTeX bibliography file was created using BibDesk.
%% http://bibdesk.sourceforge.net/


%% Created for scottl at 2007-01-06 19:23:54 -0500 


%% Saved with string encoding Western (ASCII) 


@comment{jabref-entrytype: Webpage: req[url;title] opt[author;year;keywords]}



@inproceedings{ho2000,
	Annote = {shares a lot in common with our shape-free approach.  They make use of an ensemble of simple methods that look at v/p ratio (how many partial assignments match valid words in lexicon, versus total words containing those assigned clusters).

Results are reported for business letters from the UNLV set, more than half achieve decent word accuracy (median is about 80%), but the other half fail (around 20% word accuracy).},
	Author = {<NAME> and <NAME>},
	Booktitle = {Proceedings of the 15th International Conference on Pattern Recognition (ICPR '00)},
	Date-Added = {2007-01-06 15:17:02 -0500},
	Date-Modified = {2007-01-06 15:20:42 -0500},
	Keywords = {optical character recognition, language independent approach},
	Local-Url = {ho/ho2000.pdf},
	Pages = {27--30},
	Pdf = {ho/ho2000.pdf},
	Rating = {4},
	Read = {Yes},
	Title = {OCR with no shape training},
	Volume = {4},
	Year = {2000}}

@article{hochberg1997,
	Annote = {Gets connected components of training documents, throwing out those
	with a height that is too small or too large, 
	
	rescaled to a uniform size (30x40 pixels).
	
	Uses simple clustering based on Hamming distance from training data
	then takes the average image as a template
	
	(after thresholding pixels that aren't on at least half the time).
	 
	
	Throws out clusters that don't have at least 3 elements, then attempts
	to find matches of the templates in the
	
	test set of documents.  Classifies script of document based on the
	number of matching templates.
	
	
	Results are reasonable, though the documents in the test and train
	set are often separate pages of the
	
	same document.  Has problems with unseen fonts (ex italicized roman)},
	Author = {<NAME> <NAME> <NAME> <NAME>},
	Date-Added = {2006-08-11 13:28:26 -0400},
	Date-Modified = {2007-01-04 12:16:24 -0500},
	Journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	Keywords = {script identification, document analysis, optical character recognition},
	Local-Url = {hochberg/hochberg1997.pdf},
	Number = {2},
	Pages = {176-181},
	Pdf = {hochberg/hochberg1997.pdf},
	Title = {Automatic script identification from document images using cluster-based templates},
	Volume = {19},
	Year = {1997}}

@unpublished{huang2006,
	Author = {<NAME> and McCallum, Andrew and Learned-Miller, Erik},
	Date-Added = {2006-06-13 16:16:47 -0400},
	Date-Modified = {2006-11-23 00:58:46 -0500},
	Keywords = {ocr; cryptograms},
	Local-Url = {huang/huang2006.pdf},
        Note = {UMass Technical Report 06-45},
	Month = {June},
	Pdf = {huang/huang2006.pdf},
	Rating = {5},
	Read = {Yes},
	Title = {Cryptogram Decoding for Optical Character Recognition},
	Year = {2006}}

@inproceedings{laven2005a,
	Annote = {my first published paper!},
	Author = {<NAME> and <NAME> and <NAME>},
	Booktitle = {Proceedings of the 8th International Conference on Document Analysis and Recognition},
	Date-Added = {2005-09-19 23:24:06 -0400},
	Date-Modified = {2006-10-12 11:19:23 -0400},
	Keywords = {document image analysis},
	Local-Url = {laven/laven2005a.pdf},
	Pages = {357-361},
	Pdf = {laven/laven2005a.pdf},
	Rating = {5},
	Title = {A Statistical Learning Approach To Document Image Analysis},
	Volume = {1},
	Year = {2005}}

@misc{lewis2004,
	Annote = {21,578 tagged Reuters news articles from 1987},
	Author = {<NAME>},
	Date-Added = {2007-01-06 18:54:46 -0500},
	Date-Modified = {2007-01-06 19:12:24 -0500},
	Howpublished = {electronically},
	Keywords = {dataset, reuters corpus},
	Month = {May},
	Rating = {3},
	Read = {Yes},
	Title = {Reuters-21578 Text Categorization Test Collection},
	Url = {http://www.daviddlewis.com/resources/testcollections/reuters21578/},
	Year = {2004}}

@article{nagy1987,
	Annote = {one of the earliest attempts at using a cryptogram decoding approach to performing character recognition},
	Author = {<NAME> and <NAME> and <NAME>},
	Date-Added = {2007-01-05 10:08:13 -0500},
	Date-Modified = {2007-01-05 10:10:43 -0500},
	Journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	Keywords = {cryptograms, dictionary based solution, hueristic search, optical character recognition, cryptograms},
	Number = {5},
	Pages = {710--715},
	Publisher = {IEEE Computer Society Washington, DC, USA},
	Rating = {4},
	Read = {Yes},
	Title = {Decoding substitution ciphers by means of word matching with application to OCR},
	Volume = {9},
	Year = {1987}}

@article{nartker2005,
	Annote = {outlines the UNLV ISRI dataset as well as the command line tools for testing performance.},
	Author = {<NAME>. and <NAME>. and <NAME>.},
	Date-Added = {2007-01-04 12:11:01 -0500},
	Date-Modified = {2007-01-04 12:12:59 -0500},
	Journal = {Proceedings of SPIE},
	Keywords = {optical character recognition, software tools, testing, dataset},
	Local-Url = {nartker/nartker2005.pdf},
	Pages = {37--47},
	Pdf = {nartker/nartker2005.pdf},
	Rating = {3},
	Read = {Yes},
	Title = {Software tools and test data for research and testing of page-reading OCR systems},
	Volume = {5676},
	Year = {2005}}

@book{rucklidge1996,
	Annote = {Discusses in detail the Hausdorff distance, and applies it to object detection.  There's isn't too much new information in here that isn't already covered in his other papers.},
	Author = {Rucklidge, <NAME>.},
	Date-Added = {2007-01-04 12:00:53 -0500},
	Date-Modified = {2007-01-04 12:02:47 -0500},
	Keywords = {hausdorff distance, object recognition, distance transforms},
	Number = {1173},
	Publisher = {Springer},
	Rating = {3},
	Read = {Yes},
	Series = {Lecture Notes in Computer Science},
	Title = {Efficient Visual Recognition Using the Hausdorff Distance},
	Year = {1996}}

@inproceedings{sibun1994,
	Annote = {simple yet effective method that uses x-heights and baseline offsets in common appearing words to determine language of a document.},
	Author = {<NAME> and <NAME>},
	Booktitle = {Proceedings of the 4th Conference on Applied natural language processing},
	Date-Added = {2007-01-04 12:05:46 -0500},
	Date-Modified = {2007-01-04 12:08:00 -0500},
	Keywords = {language classification, contextual analysis},
	Local-Url = {sibun/sibun1994.pdf},
	Pages = {15--21},
	Pdf = {sibun/sibun1994.pdf},
	Publisher = {M<NAME> Publishers Inc. San Francisco, CA, USA},
	Rating = {4},
	Read = {Yes},
	Title = {Language determination: natural language processing from scanned document images},
	Year = {1994}}

@article{spitz1997,
	Author = {<NAME>},
	Date-Added = {2007-01-04 11:11:05 -0500},
	Date-Modified = {2007-01-04 11:15:03 -0500},
	Journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	Keywords = {multilingual script classification, machine printed OCR, language classification, Han-based languages, Latin-based languages, Asian scripts},
	Local-Url = {spitz/spitz1997.pdf},
	Number = {3},
	Pages = {235--245},
	Pdf = {spitz/spitz1997.pdf},
	Title = {Determination of the script and language content of document images},
	Volume = {19},
	Year = {1997}}
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