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ECCV
2010
Springer
15 years 4 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
CVPR
2009
IEEE
1528views Computer Vision» more  CVPR 2009»
16 years 8 months ago
Structured Output-Associative Regression
Structured outputs such as multidimensional vectors or graphs are frequently encountered in real world pattern recognition applications such as computer vision, natural language pr...
Liefeng Bo and Cristian Sminchisescu
MICCAI
2009
Springer
15 years 11 months ago
On the Manifold Structure of the Space of Brain Images
This paper investigates an approach to model the space of brain images through a low-dimensional manifold. A data driven method to learn a manifold from a collections of brain imag...
Samuel Gerber, Tolga Tasdizen, Sarang C. Joshi, Ro...
ICCV
2005
IEEE
15 years 9 months ago
On the Spatial Statistics of Optical Flow
We develop a method for learning the spatial statistics of optical flow fields from a novel training database. Training flow fields are constructed using range images of natur...
Stefan Roth, Michael J. Black
ICMAS
2000
15 years 5 months ago
Assessing Usage Patterns to Improve Data Allocation via Auctions
The data allocation problem in incomplete information environments consisting of self-motivated servers responding to users' queries is considered. Periodically, the servers ...
Rina Azoulay-Schwartz, Sarit Kraus