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...
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...
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...
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...
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