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ICANN
2010
Springer
15 years 7 months ago
Using Reinforcement Learning to Guide the Development of Self-organised Feature Maps for Visual Orienting
We present a biologically inspired neural network model of visual orienting (using saccadic eye movements) in which targets are preferentially selected according to their reward va...
Kevin Brohan, Kevin N. Gurney, Piotr Dudek
187
Voted
PRL
2006
117views more  PRL 2006»
15 years 6 months ago
Motion features to enhance scene segmentation in active visual attention
A new computational model for active visual attention is introduced in this paper. The method extracts motion and shape features from video image sequences, and integrates these f...
María T. López, Antonio Ferná...
PRL
1998
132views more  PRL 1998»
15 years 6 months ago
Unsupervised feature selection using a neuro-fuzzy approach
A neuro-fuzzy methodology is described which involves connectionist minimization of a fuzzy feature evaluation index with unsupervised training. The concept of a ¯exible membersh...
Jayanta Basak, Rajat K. De, Sankar K. Pal
EMNLP
2009
15 years 4 months ago
Active Learning by Labeling Features
Methods that learn from prior information about input features such as generalized expectation (GE) have been used to train accurate models with very little effort. In this paper,...
Gregory Druck, Burr Settles, Andrew McCallum
AIME
2011
Springer
14 years 6 months ago
HRVFrame: Java-Based Framework for Feature Extraction from Cardiac Rhythm
Heart rate variability (HRV) analysis can be successfully applied to automatic classification of cardiac rhythm abnormalities. This paper presents a novel Java-based computer frame...
Alan Jovic, Nikola Bogunovic