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» Learning a Generative Model for Structural Representations
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ECCV
2008
Springer
14 years 9 months ago
Unsupervised Structure Learning: Hierarchical Recursive Composition, Suspicious Coincidence and Competitive Exclusion
Abstract. We describe a new method for unsupervised structure learning of a hierarchical compositional model (HCM) for deformable objects. The learning is unsupervised in the sense...
Long Zhu, Chenxi Lin, Haoda Huang, Yuanhao Chen, A...
CVPR
2009
IEEE
13 years 11 months ago
Robust unsupervised segmentation of degraded document images with topic models
Segmentation of document images remains a challenging vision problem. Although document images have a structured layout, capturing enough of it for segmentation can be difficult....
Timothy J. Burns, Jason J. Corso
EACL
2009
ACL Anthology
14 years 8 months ago
Re-Ranking Models for Spoken Language Understanding
Spoken Language Understanding aims at mapping a natural language spoken sentence into a semantic representation. In the last decade two main approaches have been pursued: generati...
Marco Dinarelli, Alessandro Moschitti, Giuseppe Ri...
ICANN
2010
Springer
13 years 8 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
SIP
2003
13 years 9 months ago
Object Structure from Noisy Images
We describe the establishment of a compound object model for object recognition purposes which provides the frame for the extraction of object structure from images degraded by no...
Gabriele Peters