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» Machine Learning for Automatic Mapping of Planetary Surfaces
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CGF
2005
252views more  CGF 2005»
13 years 7 months ago
Support Vector Machines for 3D Shape Processing
We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which...
Florian Steinke, Bernhard Schölkopf, Volker B...
ICML
2005
IEEE
14 years 8 months ago
Interactive learning of mappings from visual percepts to actions
We introduce flexible algorithms that can automatically learn mappings from images to actions by interacting with their environment. They work by introducing an image classifier i...
Justus H. Piater, Sébastien Jodogne
CVPR
2012
IEEE
11 years 10 months ago
3D landmark model discovery from a registered set of organic shapes
We present a machine learning framework that automatically generates a model set of landmarks for some class of registered 3D objects: here we use human faces. The aim is to repla...
Clement Creusot, Nick Pears, Jim Austin
MICCAI
2006
Springer
14 years 8 months ago
A Learning Based Algorithm for Automatic Extraction of the Cortical Sulci
This paper presents a learning based method for automatic extraction of the major cortical sulci from MRI volumes or extracted surfaces. Instead of using a few pre-defined rules su...
Songfeng Zheng, Zhuowen Tu, Alan L. Yuille, Allan ...
DAGSTUHL
2009
13 years 8 months ago
Learning Highly Structured Manifolds: Harnessing the Power of SOMs
Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...
Erzsébet Merényi, Kadim Tasdemir, Li...