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ICDAR
2007
IEEE
14 years 1 months ago
A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images
We describe an unsupervised learning algorithm for extracting sparse and locally shift-invariant features. We also devise a principled procedure for learning hierarchies of invari...
Marc'Aurelio Ranzato, Yann LeCun
BMCBI
2007
163views more  BMCBI 2007»
13 years 7 months ago
A coherent graph-based semantic clustering and summarization approach for biomedical literature and a new summarization evaluati
Background: A huge amount of biomedical textual information has been produced and collected in MEDLINE for decades. In order to easily utilize biomedical information in the free t...
Illhoi Yoo, Xiaohua Hu, Il-Yeol Song
CIARP
2005
Springer
14 years 1 months ago
A Robust Free Size OCR for Omni-Font Persian/Arabic Printed Document Using Combined MLP/SVM
Optical character recognition of cursive scripts present a number of challenging problems in both segmentation and recognition processes and this attracts many researches in the fi...
Hamed Pirsiavash, Ramin Mehran, Farbod Razzazi
CIKM
2008
Springer
13 years 9 months ago
Integrating clustering and multi-document summarization to improve document understanding
Document understanding techniques such as document clustering and multi-document summarization have been receiving much attention in recent years. Current document clustering meth...
Dingding Wang, Shenghuo Zhu, Tao Li, Yun Chi, Yiho...
ICDAR
1999
IEEE
13 years 11 months ago
Document Image Layout Comparison and Classification
This paper describes features and methods for document image comparison and classification at the spatial layout level. The methods are useful for visual similarity based document...
Jianying Hu, Ramanujan S. Kashi, Gordon T. Wilfong