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» Learning a Generative Model for Structural Representations
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CAD
2004
Springer
13 years 7 months ago
A multi-resolution topological representation for non-manifold meshes
We address the problem of representing and processing 3D objects, described through simplicial meshes, which consist of parts of mixed dimensions, and with a non-manifold topology...
Leila De Floriani, Paola Magillo, Enrico Puppo, Da...
KCAP
2005
ACM
14 years 1 months ago
AutoFeed: an unsupervised learning system for generating webfeeds
The AutoFeed system automatically extracts data from semistructured web sites. Previously, researchers have developed two types of supervised learning approaches for extracting we...
Bora Gazen, Steven Minton
IJCAI
2007
13 years 9 months ago
Incremental Construction of Structured Hidden Markov Models
This paper presents an algorithm for inferring a Structured Hidden Markov Model (S-HMM) from a set of sequences. The S-HMMs are a sub-class of the Hierarchical Hidden Markov Model...
Ugo Galassi, Attilio Giordana, Lorenza Saitta
ICCV
2003
IEEE
14 years 9 months ago
A Multi-scale Generative Model for Animate Shapes and Parts
This paper presents a multi-scale generative model for representing animate shapes and extracting meaningful parts of objects. The model assumes that animate shapes (2D simple clo...
Aleksandr Dubinskiy, Song Chun Zhu
DCC
2011
IEEE
13 years 2 months ago
Robust Learning of 2-D Separable Transforms for Next-Generation Video Coding
With the simplicity of its application together with compression efficiency, the Discrete Cosine Transform(DCT) plays a vital role in the development of video compression standar...
Osman Gokhan Sezer, Robert A. Cohen, Anthony Vetro