Pattern classification with compact distribution maps
Computer Vision and Image Understanding
Twenty Years of Document Image Analysis in PAMI
IEEE Transactions on Pattern Analysis and Machine Intelligence
Complexity Measures of Supervised Classification Problems
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Dependence of Handwritten Word Recognizers on Lexicons
IEEE Transactions on Pattern Analysis and Machine Intelligence
Relating Statistical Image Differences and Degradation Features
DAS '02 Proceedings of the 5th International Workshop on Document Analysis Systems V
Human Interactive Proofs and Document Image Analysis
DAS '02 Proceedings of the 5th International Workshop on Document Analysis Systems V
Complexity of Classification Problems and Comparative Advantages of Combined Classifiers
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Toward a Computational Theory of Data Acquisition and Truthing
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Estimating Degradation Model Parameters from Character Images
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Robust document image understanding technologies
Proceedings of the 1st ACM workshop on Hardcopy document processing
Text Degradations and OCR Training
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Performance characterization in computer vision: A guide to best practices
Computer Vision and Image Understanding
DIAR: Advances in Degradation Modeling and Processing
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Data Complexity Analysis: Linkage between Context and Solution in Classification
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Constructing ensembles of classifiers by means of weighted instance selection
IEEE Transactions on Neural Networks
A novel method to determine scanner parameters (PSF)
ACOS'06 Proceedings of the 5th WSEAS international conference on Applied computer science
Towards versatile document analysis systems
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
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Many obstacles to progress in image pattern recognition result from the fact that per-class distributions are often too irregular to be well-approximated by simple analytical functions. Simulation studies offer one way to circumvent these obstacles. We present three closely related studies of machine-printed character recognition that rely on synthetic data generated pseudorandomly in accordance with an explicit stochastic model of document image degradations. The unusually large scale of experiments驴involving several million samples驴that this methodology makes possible has allowed us to compute sharp estimates of the intrinsic difficulty (Bayes risk) of concrete image recognition problems, as well as the asymptotic accuracy and domain of competency of classifiers.