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123
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CVPR
2007
IEEE
16 years 4 months ago
Learning Gaussian Conditional Random Fields for Low-Level Vision
Markov Random Field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented u...
Marshall F. Tappen, Ce Liu, Edward H. Adelson, Wil...
99
Voted
ICCV
2007
IEEE
16 years 4 months ago
Limits of Learning-Based Superresolution Algorithms
Learning-based superresolution (SR) are popular SR techniques that use application dependent priors to infer the missing details in low resolution images (LRIs). However, their pe...
Zhouchen Lin, Junfeng He, Xiaoou Tang, Chi-Keung T...
BPM
2005
Springer
102views Business» more  BPM 2005»
15 years 8 months ago
Integrating Process Learning and Process Evolution - A Semantics Based Approach
Companies are developing a growing interest in aligning their information systems in a process-oriented way. However, current processaware information systems (PAIS) fail to meet p...
Stefanie Rinderle, Barbara Weber, Manfred Reichert...
131
Voted
AI
1998
Springer
15 years 6 months ago
ELEM2: A Learning System for More Accurate Classifications
We present ELEM2, a new method for inducing classification rules from a set of examples. The method employs several new strategies in the induction and classification processes to ...
Aijun An, Nick Cercone
103
Voted
LREC
2008
253views Education» more  LREC 2008»
15 years 4 months ago
Learning properties of Noun Phrases: from data to functions
The paper presents two experiments of unsupervised classification of Italian noun phrases. The goal of the experiments is to identify the most prominent contextual properties that...
Valeria Quochi, Basilio Calderone