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» Learning the Relative Importance of Features in Image Data
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157
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AUSAI
2008
Springer
15 years 6 months ago
Character Recognition Using Hierarchical Vector Quantization and Temporal Pooling
In recent years, there has been a cross-fertilization of ideas between computational neuroscience models of the operation of the neocortex and artificial intelligence models of mac...
John Thornton, Jolon Faichney, Michael Blumenstein...
246
Voted
ICDE
2006
IEEE
207views Database» more  ICDE 2006»
16 years 6 months ago
Automatic Sales Lead Generation from Web Data
Speed to market is critical to companies that are driven by sales in a competitive market. The earlier a potential customer can be approached in the decision making process of a p...
Ganesh Ramakrishnan, Sachindra Joshi, Sumit Negi, ...
IJCNN
2006
IEEE
15 years 10 months ago
Training of Large-Scale Feed-Forward Neural Networks
Abstract— Neural processing of large-scale data sets containing both many input / output variables and a large number of training examples often leads to very large networks. Onc...
Udo Seiffert
164
Voted
ECCV
2008
Springer
15 years 6 months ago
Unsupervised Classification and Part Localization by Consistency Amplification
We present a novel method for unsupervised classification, including the discovery of a new category and precise object and part localization. Given a set of unlabelled images, som...
Leonid Karlinsky, Michael Dinerstein, Dan Levi, Sh...
167
Voted
AGENTS
1998
Springer
15 years 8 months ago
Learning Situation-Dependent Costs: Improving Planning from Probabilistic Robot Execution
Physical domains are notoriously hard to model completely and correctly, especially to capture the dynamics of the environment. Moreover, since environments change, it is even mor...
Karen Zita Haigh, Manuela M. Veloso