E
E. Kleinberg
Researcher at State University of New York System
Publications - 6
Citations - 198
E. Kleinberg is an academic researcher from State University of New York System. The author has contributed to research in topics: Word recognition & Statistical classification. The author has an hindex of 4, co-authored 6 publications receiving 179 citations. Previous affiliations of E. Kleinberg include University at Buffalo.
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Journal ArticleDOI
On the algorithmic implementation of stochastic discrimination
TL;DR: An outline of the underlying mathematical theory of stochastic discrimination is outlined and a remark concerning boosting is made, which provides a theoretical justification for properties of that method observed in practice, including its ability to generalize.
Journal ArticleDOI
Holistic verification of handwritten phrases
TL;DR: A system for rapid verification of unconstrained off-line handwritten phrases using perceptual holistic features of the handwritten phrase image using heuristic rules to verify handwritten street names automatically extracted from live US mail against recognition results of analytical classifiers.
Proceedings ArticleDOI
The HOVER system for rapid holistic verification of off-line handwritten phrases
TL;DR: In this article, a system for rapid verification of unconstrained off-line handwritten phrases using perceptual holistic features of the handwritten phrase image is described, which is used to verify handwritten street names automatically extracted from live US mail against recognition results of analytical classifiers.
Journal ArticleDOI
Empirical Design of a Multi-Classifier Thresholding/Control Strategy for Recognition of Handwritten Street Names
TL;DR: In this paper, the authors describe an empirical approach to the design of a multi-classifier HWR thresholding/control module which forms part of a real-time handwritten address interpretation (HWAI) system.
Journal Article
HOVER system for rapid holistic verification of off-line handwritten phrases
TL;DR: The authors describe ongoing research on a system for rapid verification of unconstrained off-line handwritten phrases using perceptual holistic features of the handwritten phrase image to reject errors with 98% accuracy at the 30% accept level.