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ISI
2006
Springer
15 years 6 months ago
An Embedded Bayesian Network Hidden Markov Model for Digital Forensics
In the paper we combine a Bayesian Network model for encoding forensic evidence during a given time interval with a Hidden Markov Model (EBN-HMM) for tracking and predicting the de...
Olivier Y. de Vel, Nianjun Liu, Terry Caelli, Tib&...
CPHYSICS
2007
89views more  CPHYSICS 2007»
15 years 6 months ago
Numerical differentiation of experimental data: local versus global methods
In the context of the analysis of measured data, one is often faced with the task to differentiate data numerically. Typically, this occurs when measured data are concerned or dat...
Karsten Ahnert, Markus Abel
JISE
2008
77views more  JISE 2008»
15 years 6 months ago
Formalized Entity Extraction Methodology for Changeable Business Requirements
business requirement in the real world cannot be abstracted correctly into an entity-relationship schema. Once core entities are discovered, we can obtain an Entity-Relationship Di...
Namgyu Kim, Sangwon Lee, Songchun Moon
IVC
2006
120views more  IVC 2006»
15 years 6 months ago
Face recognition by fusing thermal infrared and visible imagery
Thermal infrared (IR) imagery offers a promising alternative to visible imagery for face recognition due to its relative insensitive to variations in face appearance caused by ill...
George Bebis, Aglika Gyaourova, Saurabh Singh, Ioa...
JMLR
2008
230views more  JMLR 2008»
15 years 6 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
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