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» A Statistical Learning Approach To Document Image Analysis
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IDEAL
2005
Springer
15 years 5 months ago
Kernel Biased Discriminant Analysis Using Histogram Intersection Kernel for Content-Based Image Retrieval
It is known that no single descriptor is powerful enough to encompass all aspects of image content, i.e. each feature extraction method has its own view of the image content. A pos...
Lin Mei, Gerd Brunner, Lokesh Setia, Hans Burkhard...
ICDAR
2003
IEEE
15 years 5 months ago
Gabor Filter Based Multi-class Classifier for Scanned Document Images
When scanning documents with a large number of pages such as books, it is often feasible to provide a minimal number of training samples to personalize the system to compensate fo...
Huanfeng Ma, David S. Doermann
SG
2007
Springer
15 years 6 months ago
Correlating Text and Images: Concept and Evaluation
This paper presents the concept and an evaluation of a novel approach to support students to understand complex spatial relations and to learn unknown terms of a domain-specific t...
Timo Götzelmann, Pere-Pau Vázquez, Knu...
ICDAR
2003
IEEE
15 years 5 months ago
Improvement of Matching and Evaluation in Handwritten Numeral Recognition Using Flexible Standard Patterns
The purpose of this study is to develop a flexible matching method for recognizing handwritten numerals based on the statistics of shapes and structures learned from learning sam...
Hirokazu Muramatsu, Takashi Kobayashi, Takahiro Su...
CVPR
2005
IEEE
16 years 1 months ago
Multilinear Independent Components Analysis
Independent Components Analysis (ICA) maximizes the statistical independence of the representational components of a training image ensemble, but it cannot distinguish between the...
M. Alex O. Vasilescu, Demetri Terzopoulos