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CVPR
2008
IEEE
16 years 8 months ago
The Logistic Random Field - A convenient graphical model for learning parameters for MRF-based labeling
Graphical models are fundamental tools for modeling images and other applications. In this paper, we propose the Logistic Random Field (LRF) model for representing a discrete-valu...
Marshall F. Tappen, Kegan G. G. Samuel, Craig V. D...
ICCV
1998
IEEE
16 years 8 months ago
Sectored Snakes: Evaluating Learned-Energy Segmentations
We describe how to teach deformable models to maximize image segmentation correctness based on user-specified criteria, and we present a method for evaluating which criteria work ...
Samuel D. Fenster, John R. Kender
183
Voted
ECCV
2008
Springer
16 years 8 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
203
Voted
ECCV
2006
Springer
16 years 8 months ago
Globally Optimal Active Contours, Sequential Monte Carlo and On-Line Learning for Vessel Segmentation
In this paper we propose a Particle Filter-based propagation approach for the segmentation of vascular structures in 3D volumes. Because of pathologies and inhomogeneities, many de...
Charles Florin, Nikos Paragios, James Williams
ECCV
2006
Springer
16 years 8 months ago
Learning Discriminative Canonical Correlations for Object Recognition with Image Sets
Abstract. We address the problem of comparing sets of images for object recognition, where the sets may represent arbitrary variations in an object's appearance due to changin...
Tae-Kyun Kim, Josef Kittler, Roberto Cipolla