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ICCV
2007
IEEE
16 years 8 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...
MM
2005
ACM
209views Multimedia» more  MM 2005»
16 years 3 days ago
Learning an image-word embedding for image auto-annotation on the nonlinear latent space
Latent Semantic Analysis (LSA) has shown encouraging performance for the problem of unsupervised image automatic annotation. LSA conducts annotation by keywords propagation on a l...
Wei Liu, Xiaoou Tang
213
Voted
ECAI
2004
Springer
15 years 12 months ago
Learning Complex and Sparse Events in Long Sequences
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
Marco Botta, Ugo Galassi, Attilio Giordana
195
Voted
ICADL
2003
Springer
159views Education» more  ICADL 2003»
15 years 11 months ago
Ontology Learning for Medical Digital Libraries
Ontologies play an important role in the Semantic Web as well as in digital library and knowledge portal applications. This project seeks to develop an automatic method to enrich e...
Chew-Hung Lee, Jin-Cheon Na, Christopher S. G. Kho...
149
Voted
UIST
1994
ACM
15 years 10 months ago
Evolutionary Learning of Graph Layout Constraints from Examples
We propose a new evolutionary method of extracting user preferences from examples shown to an automatic graph layout system. Using stochastic methods such as simulated annealing a...
Toshiyuki Masui