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WACV
2005
IEEE
15 years 6 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 8 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 3 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 6 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 2 months 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