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ICCV
2007
IEEE
15 years 27 days ago
Fitting a Morphable Model to 3D Scans of Faces
This paper presents a top-down approach to 3D data analysis by fitting a Morphable Model to scans of faces. In a unified framework, the algorithm optimizes shape, texture, pose an...
Volker Blanz, Kristina Scherbaum, Hans-Peter Seide...
ICPR
2008
IEEE
15 years 4 days ago
Feature Fusion Hierarchies for gender classification
We present a hierarchical feature fusion model for image classification that is constructed by an evolutionary learning algorithm. The model has the ability to combine local patch...
Fabien Scalzo, George Bebis, Mircea Nicolescu, Lea...
ICPR
2004
IEEE
15 years 1 days ago
Hierarchical Object Indexing and Sequential Learning
This work is about scene interpretation in the sense of detecting and localizing instances from multiple object classes. We concentrate on object indexing: generate an over-comple...
Donald Geman, Xiaodong Fan
ICML
1998
IEEE
14 years 11 months ago
The MAXQ Method for Hierarchical Reinforcement Learning
This paper presents a new approach to hierarchical reinforcement learning based on the MAXQ decomposition of the value function. The MAXQ decomposition has both a procedural seman...
Thomas G. Dietterich
OOPSLA
2007
Springer
14 years 5 months ago
No ifs, ands, or buts: uncovering the simplicity of conditionals
Schematic tables are a new representation for conditionals. Roughly a cross between decision tables and data flow graphs, they represent computation and decision-making orthogona...
Jonathan Edwards