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CVPR
2010
IEEE
16 years 3 months ago
Learning Full Pairwise Affinities for Spectral Segmentation
This paper studies the problem of learning a full range of pairwise affinities gained by integrating local grouping cues for spectral segmentation. The overall quality of the spect...
Tae Hoon Kim (Seoul National University), Kyoung M...
CIKM
2009
Springer
16 years 1 months ago
A machine learning approach for improved BM25 retrieval
Despite the widespread use of BM25, there have been few studies examining its effectiveness on a document description over single and multiple field combinations. We determine t...
Krysta Marie Svore, Christopher J. C. Burges
ICCV
2007
IEEE
16 years 1 months ago
Shape Priors using Manifold Learning Techniques
We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a category o...
Patrick Etyngier, Florent Ségonne, Renaud K...
ICFEM
2004
Springer
16 years 2 days ago
Learning to Verify Safety Properties
We present a novel approach for verifying safety properties of finite state machines communicating over unbounded FIFO channels that is based on applying machine learning techniqu...
Abhay Vardhan, Koushik Sen, Mahesh Viswanathan, Gu...
ACCV
1998
Springer
15 years 11 months ago
Learning Multiscale Image Models of 2D Object Classes
This paper isconcerned with learning the canonical gray scalestructure of the images of a classof objects. Structure is defined in terms of the geometry and layout of salientimage...
Benoit Perrin, Narendra Ahuja, Narayan Srinivasa