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WACV
2005
IEEE
15 years 5 months ago
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Thomas S. Stepleton, Tai Sing Lee
EVOW
2009
Springer
15 years 6 months ago
Evolutionary Optimization Guided by Entropy-Based Discretization
The Learnable Evolution Model (LEM) involves alternating periods of optimization and learning, performa extremely well on a range of problems, a specialises in achieveing good resu...
Guleng Sheri, David W. Corne
CVPR
2008
IEEE
16 years 1 months ago
Combining appearance models and Markov Random Fields for category level object segmentation
Object models based on bag-of-words representations can achieve state-of-the-art performance for image classification and object localization tasks. However, as they consider obje...
Diane Larlus, Frédéric Jurie
SPIN
2004
Springer
15 years 5 months ago
Explicit State Model Checking with Hopper
The Murϕ-based Hopper tool is a general purpose explicit model checker. Hopper leverages Murϕ’s class structure to implement new algorithms. Hopper differs from Murϕ in that i...
Michael Jones, Eric Mercer
ICPR
2004
IEEE
16 years 26 days ago
Perceptual Grouping for Contour Extraction
This paper describes an algorithm that efficiently groups line segments into perceptually salient contours in complex images. A measure of affinity between pairs of lines is used ...
Francisco J. Estrada, Allan D. Jepson