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JMLR
2012
11 years 8 months ago
Bounding the Probability of Error for High Precision Optical Character Recognition
We consider a model for which it is important, early in processing, to estimate some variables with high precision, but perhaps at relatively low recall. If some variables can be ...
Gary B. Huang, Andrew Kae, Carl Doersch, Erik G. L...
SCALESPACE
2007
Springer
14 years 4 days ago
Uniform and Textured Regions Separation in Natural Images Towards MPM Adaptive Denoising
Abstract. Natural images consist of texture, structure and smooth regions and this makes the task of filtering challenging mainly when it aims at edge and texture preservation. In...
Noura Azzabou, Nikos Paragios, Frederic Guichard
ICASSP
2011
IEEE
12 years 9 months ago
On selecting the hyperparameters of the DPM models for the density estimation of observation errors
The Dirichlet Process Mixture (DPM) models represent an attractive approach to modeling latent distributions parametrically. In DPM models the Dirichlet process (DP) is applied es...
Asma Rabaoui, Nicolas Viandier, Juliette Marais, E...
IEEEARES
2010
IEEE
14 years 26 days ago
A Complexity Based Model for Quantifying Forensic Evidential Probabilities
- An operational complexity model (OCM) is proposed to enable the complexity of both the cognitive and the computational components of a process to be determined. From the complexi...
Richard E. Overill, Jantje A. M. Silomon, Kam-Pui ...
PRL
2008
85views more  PRL 2008»
13 years 6 months ago
Reliability estimation of a statistical classifier
Pattern classification techniques derived from statistical principles have been widely studied and have proven powerful in addressing practical classification problems. In real-wo...
Pandu Ranga Rao Devarakota, Bruno Mirbach, Bjö...