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» A Statistical Learning Approach To Document Image Analysis
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NIPS
2000
15 years 1 months ago
Learning Joint Statistical Models for Audio-Visual Fusion and Segregation
People can understand complex auditory and visual information, often using one to disambiguate the other. Automated analysis, even at a lowlevel, faces severe challenges, includin...
John W. Fisher III, Trevor Darrell, William T. Fre...
ICDAR
2009
IEEE
15 years 6 months ago
A Modified Adaptive Logical Level Binarization Technique for Historical Document Images
In this paper, a new document image binarization technique is presented, as an improved version of the state-of-the-art adaptive logical level technique (ALLT). The original ALLT ...
Konstantinos Ntirogiannis, Basilios Gatos, Ioannis...
ICDAR
2007
IEEE
15 years 1 months ago
Example-Based Logical Labeling of Document Title Page Images
This paper presents a flexible and effective examplebased approach for labeling title pages which can be used for automated extraction of bibliographic data. The labels of intere...
Joost van Beusekom, Daniel Keysers, Faisal Shafait...
ICDAR
2007
IEEE
15 years 6 months ago
Handwritten Word Recognition Using Conditional Random Fields
The paper describes a lexicon driven approach for word recognition on handwritten documents using Conditional Random Fields(CRFs). CRFs are discriminative models and do not make a...
Shravya Shetty, Harish Srinivasan, Sargur N. Sriha...
CVPR
2009
IEEE
15 years 3 months ago
Robust unsupervised segmentation of degraded document images with topic models
Segmentation of document images remains a challenging vision problem. Although document images have a structured layout, capturing enough of it for segmentation can be difficult....
Timothy J. Burns, Jason J. Corso