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» Layered Object Models for Image Segmentation
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ICML
2009
IEEE
15 years 10 months ago
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...
ICPR
2010
IEEE
15 years 1 months ago
The Fusion of Deep Learning Architectures and Particle Filtering Applied to Lip Tracking
This work introduces a new pattern recognition model for segmenting and tracking lip contours in video sequences. We formulate the problem as a general nonrigid object tracking me...
Gustavo Carneiro, Jacinto Nascimento
ISBI
2009
IEEE
15 years 4 months ago
Morphometric Subtyping for a Panel of Breast Cancer Cell Lines
A panel of cell lines of diverse molecular background offers an improved model system for high-content screening, comparative analysis, and cell systems biology. A computational p...
Ju Han, Hang Chang, Gerald Fontenay, Nicholas J. W...
PAMI
2010
205views more  PAMI 2010»
14 years 8 months ago
Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
Long Zhu, Yuanhao Chen, Alan L. Yuille
CVPR
2011
IEEE
14 years 6 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...