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» A reinforcement learning model of selective visual attention
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ICRA
2009
IEEE
173views Robotics» more  ICRA 2009»
14 years 2 months ago
Most salient region tracking
— In this paper, we introduce a cognitive approach for object tracking from a mobile platform. The approach is based on a biologically motivated attention system which is able to...
Simone Frintrop, Markus Kessel
IJCNN
2000
IEEE
13 years 11 months ago
Competing Hidden Markov Models on the Self-Organizing Map
This paper presents an unsupervised segmentation method for feature sequences based on competitivelearning hidden Markov models. Models associated with the nodes of the Self-Organ...
Panu Somervuo
IJON
2006
76views more  IJON 2006»
13 years 7 months ago
Joint maps for orientation, eye, and direction preference in a self-organizing model of V1
Primary visual cortex (V1) contains overlaid feature maps for orientation (OR), motion direction selectivity (DR), and ocular dominance (OD). Neurons in these maps are connected l...
James A. Bednar, Risto Miikkulainen
SDM
2012
SIAM
216views Data Mining» more  SDM 2012»
11 years 10 months ago
Feature Selection "Tomography" - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable
:  Feature Selection “Tomography” - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable George Forman HP Laboratories HPL-2010-19R1 Feature selection; ...
George Forman
CVPR
2012
IEEE
11 years 10 months ago
Weakly supervised structured output learning for semantic segmentation
We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test im...
Alexander Vezhnevets, Vittorio Ferrari, Joachim M....