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CLEIEJ
2008
82views more  CLEIEJ 2008»
14 years 9 months ago
Postal Envelope Segmentation using Learning-Based Approach
This paper presents a learning-based approach to segment postal address blocks where the learning step uses only one pair of images (a sample image and its ideal segmented solutio...
Horacio Andrés Legal-Ayala, Jacques Facon, ...
NN
2006
Springer
163views Neural Networks» more  NN 2006»
14 years 9 months ago
Machine learning approaches for estimation of prediction interval for the model output
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
Durga L. Shrestha, Dimitri P. Solomatine
78
Voted
CIKM
1997
Springer
15 years 1 months ago
Learning Belief Networks from Data: An Information Theory Based Approach
This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
Jie Cheng, David A. Bell, Weiru Liu
NN
2006
Springer
114views Neural Networks» more  NN 2006»
14 years 9 months ago
Modular learning models in forecasting natural phenomena
Modular model is a particular type of committee machine and is comprised of a set of specialized (local) models each of which is responsible for a particular region of the input s...
Dimitri P. Solomatine, Michael Baskara L. A. Siek
DAC
2006
ACM
14 years 11 months ago
Systematic software-based self-test for pipelined processors
Software-based self-test (SBST) has recently emerged as an effective methodology for the manufacturing test of processors and other components in systems-on-chip (SoCs). By moving ...
Mihalis Psarakis, Dimitris Gizopoulos, Miltiadis H...