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» Structured Objects: Modeling and Reasoning
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NIPS
2004
15 years 5 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
HLK
2003
IEEE
15 years 9 months ago
Bayesian Reconstruction of 3D Shapes and Scenes From A Single Image
It’s common experience for human vision to perceive full 3D shape and scene from a single 2D image with the occluded parts “filled-in” by prior visual knowledge. In this pa...
Feng Han, Song Chun Zhu
FLAIRS
2004
15 years 5 months ago
Cellular Automata Approach to Aircraft Corrosion Pit Growth
Corrosion is one of the degrading mechanisms that greatly affect the structural integrity of aerospace components. Corrosion begins with small imperfections in the given material ...
Ramana Pidaparti, Mathew J. Palakal, Long Fong
NIPS
2001
15 years 5 months ago
Convolution Kernels for Natural Language
We describe the application of kernel methods to Natural Language Processing (NLP) problems. In many NLP tasks the objects being modeled are strings, trees, graphs or other discre...
Michael Collins, Nigel Duffy
SMA
2009
ACM
157views Solid Modeling» more  SMA 2009»
15 years 10 months ago
Constraint-based model synthesis
We present a method for procedurally modeling general complex 3D shapes. Our approach is targeted towards applications in digital entertainment and gaming and can automatically ge...
Paul Merrell, Dinesh Manocha