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GECCO
2009
Springer
13 years 9 months ago
The sensitivity of HyperNEAT to different geometric representations of a problem
HyperNEAT, a generative encoding for evolving artificial neural networks (ANNs), has the unique and powerful ability to exploit the geometry of a problem (e.g., symmetries) by enc...
Jeff Clune, Charles Ofria, Robert T. Pennock

Publication
519views
12 years 2 months ago
The Finite Volume, Finite Difference, and Finite Elements Methods as Numerical Methods for Physical Field Problems
I. Introduction II. Foundations A. The Mathematical Structure of Physical Field Theories B. Geometric Objects and Orientation 1. Space-Time Object...
Claudio Mattiussi
IJCV
2000
225views more  IJCV 2000»
13 years 4 months ago
Depth from Defocus vs. Stereo: How Different Really Are They?
Depth from Focus (DFF) and Depth from Defocus (DFD) methods are theoretically unified with the geometric triangulation principle. Fundamentally, the depth sensitivities of DFF and ...
Yoav Y. Schechner, Nahum Kiryati
AMC
2007
125views more  AMC 2007»
13 years 4 months ago
Geometric multigrid for high-order regularizations of early vision problems
The surface estimation problem is used as a model to demonstrate a framework for solving early vision problems by high-order regularization with natural boundary conditions. Becaus...
Stephen L. Keeling, Gundolf Haase
CVPR
2000
IEEE
13 years 8 months ago
Matching Images with Different Resolutions
In this paper we address the problem of matching two images with two different resolutions: a high-resolution image and a low-resolution one. On the premise that changes in resolu...
Yves Dufournaud, Cordelia Schmid, Radu Horaud