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» Level Set Methods for Dynamic Tomography
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ECAI
2010
Springer
13 years 5 months ago
From bursty patterns to bursty facts: The effectiveness of temporal text mining for news
Many document collections are by nature dynamic, evolving as the topics or events they describe change. The goal of temporal text mining is to discover bursty patterns and to ident...
Ilija Subasic, Bettina Berendt
IAT
2009
IEEE
14 years 2 months ago
Symbol Statistics for Concept Formation in AI Agents
—High level conceptual thought seems to be at the basis of the impressive human cognitive ability. Classical topdown (Logic based) and bottom-up (Connectionist) approaches to the...
Jason R. Chen
ICPR
2000
IEEE
14 years 3 days ago
Feature Learning for Recognition with Bayesian Networks
Many realistic visual recognition tasks are “open” in the sense that the number and nature of the categories to be learned are not initially known, and there is no closed set ...
Justus H. Piater, Roderic A. Grupen
BMCBI
2006
127views more  BMCBI 2006»
13 years 7 months ago
On the attenuation and amplification of molecular noise in genetic regulatory networks
Background: Noise has many important roles in cellular genetic regulatory functions at the nanomolar scale. At present, no good theory exists for identifying all possible mechanis...
Bor-Sen Chen, Yu-Chao Wang
SMI
2008
IEEE
255views Image Analysis» more  SMI 2008»
14 years 2 months ago
GPU-accelerated surface denoising and morphing with lattice Boltzmann scheme
In this paper, we introduce a parallel numerical scheme, the lattice Boltzmann method, to shape modeling applications. The motivation of using this originally-designed fluid dyna...
Ye Zhao