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Daniel
X
Le
,
PhD
Electronics Engineer
Location: 
38A
/
10S1018
Phone Number: (
301
435-3210
Expertise and Research Interests: 

Daniel X. Le received the BS degree summa cum laude in Electrical and Computer Engineering from California State Polytechnic University, Pomona, in June 1986 and the MS and PhD degrees in Computer Science from George Mason University, Fairfax, Virginia, in January 1993 and February 1997, respectively.

From June 1986 to April 1989, he was a software engineer at the Jet Propulsion Laboratory, Pasadena, California. From April 1989 to September 1990, he was a system engineer at Science Applications International Corporation, McLean, Virginia. Since September 1990, he has been an electronics engineer here at the Lister Hill National Center for Biomedical Communications, the research and development arm of the National Library of Medicine. 

Dr. Le's research interests are in document analysis and understanding, neural networks, optical character recognition, image quality and image processing. Dr. Le holds one US patent on automated portrait/landscape orientation detection in binary document images.

Publications/Tools by Daniel Le: 
Kim I, Le DX, Thoma GR. Automated method for extracting "citation sentences" from online biomedical articles using SVM-based text summarization technique. Proc. the 2014 IEEE Int'l Conf. on Systems, Man, and Cybernetics (SMC 2014), pp. 2006-2011, San Diego, October, 2014
Kim J, Le DX, Thoma GR. Identification of Investigator Name Zones Using SVM Classifiers and Heuristic Rules. 12th international Conference on Document Analysis and Recognition (ICDAR). Washington D.C., August 2013.
Zhang X, Zou J, Le DX, Thoma GR. Combining Discriminative SVM models for the Improved Recognition of Investigator Names in Medical Articles. Proceedings of SPIE Volume 8658, Document Recognition and Retrieval XX, IS&T/SPIE Electronic Imaging 2013.
Kim I, Le DX, Thoma GR. Identifying “comment-on” citation data in online biomedical articles using SVM-based text summarization technique. Proc. Int’l Conf. Artificial Intelligence (ICAI’12), vol. 1, pp. 431-437, Las Vegas, July 2012.
Kim J, Le DX, Thoma GR. Combining SVM Classifiers to Identify Investigator Name Zones in Biomedical Articles. IS&T/SPIE’s 22nd Annual Symposium on Electronic Imaging. San Francisco, CA, January 2012; 8297.
Zhang X, Zou J, Le DX, Thoma GR. A structural SVM approach for reference parsing. BMC Bioinformatics. 2011 Jun 9;12 Suppl 3:S7. doi: 10.1186/1471-2105-12-S3-S7.
Kim I, Le DX, Thoma GR. Automated identification of biomedical article type using support vector machines. Proc. 18th SPIE Document Recognition and Retrieval, 7874:787403 (1-9), San Francisco, January 2011.
Zhang X, Zou J, Le DX, Thoma GR. Investigator Name Recognition From Medical Journal Articles: A Comparative Study of SVM and Structural SVM International Workshop on Document Analysis Systems. June 2010:121-8
Zou J, Le DX, Thoma GR. Locating and parsing bibliographic references in HTML medical articles. Int J Doc Anal Recognit. 2010 Jun 1;13(2):107-119.
Kim J, Le DX, Thoma GR. Naive Bayes and SVM Classifiers For Classifying Databank Accession Number Sentences From Online Biomedical Articles IS&T/SPIE's 22nd Annual Symposium on Electronic Imaging. San Jose, CA. January 2010;7534:75340U-1 - 8

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