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» Models for Incomplete and Probabilistic Information
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219
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CVPR
2011
IEEE
14 years 9 months ago
Nonlinear Shape Manifolds as Shape Priors in Level Set Segmentation and Tracking
We propose a novel nonlinear, probabilistic and variational method for adding shape information to level setbased segmentation and tracking. Unlike previous work, we represent sha...
Victor Prisacariu, Ian Reid
KDD
2003
ACM
449views Data Mining» more  KDD 2003»
16 years 6 months ago
Passenger-based predictive modeling of airline no-show rates
Airlines routinely overbook flights based on the expectation that some fraction of booked passengers will not show for each flight. Accurate forecasts of the expected number of no...
Richard D. Lawrence, Se June Hong, Jacques Cherrie...
BMCBI
2008
137views more  BMCBI 2008»
15 years 6 months ago
A dynamic Bayesian network approach to protein secondary structure prediction
Background: Protein secondary structure prediction method based on probabilistic models such as hidden Markov model (HMM) appeals to many because it provides meaningful informatio...
Xin-Qiu Yao, Huaiqiu Zhu, Zhen-Su She
189
Voted
FASE
2005
Springer
15 years 11 months ago
Using Scenarios to Predict the Reliability of Concurrent Component-Based Software Systems
Scenarios are a popular means for capturing behavioural requirements of software systems early in the lifecycle. Scenarios show how components interact to provide system level func...
Genaína Nunes Rodrigues, David S. Rosenblum...
167
Voted
NN
2006
Springer
141views Neural Networks» more  NN 2006»
15 years 5 months ago
Encoding uncertainty in the hippocampus
The medial temporal lobe may play a critical role in binding successive events into memory while encoding contextual information in implicit and explicit memory tasks. Information...
Lee M. Harrison, Andrew Duggins, Karl J. Friston