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» Markov Random Field Models in Computer Vision
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ICPR
2010
IEEE
14 years 11 months ago
Cross Entropy Optimization of the Random Set Framework for Multiple Instance Learning
Abstract--Multiple instance learning (MIL) is a recently researched technique used for learning a target concept in the presence of noise. Previously, a random set framework for mu...
Jeremy Bolton, Paul D. Gader
IFM
2010
Springer
190views Formal Methods» more  IFM 2010»
15 years 8 days ago
On Model Checking Techniques for Randomized Distributed Systems
Abstract. The automata-based model checking approach for randomized distributed systems relies on an operational interleaving semantics of the system by means of a Markov decision ...
Christel Baier
EPEW
2006
Springer
15 years 5 months ago
A Precedence PEPA Model for Performance and Reliability Analysis
We propose new techniques to simplify the computation of the cycle times and the absorption times for a large class of PEPA models. These techniques allow us to simplify the model ...
Jean-Michel Fourneau, Leïla Kloul
CVPR
2007
IEEE
16 years 3 months ago
Real-time Gesture Recognition with Minimal Training Requirements and On-line Learning
In this paper, we introduce the semantic network model (SNM), a generalization of the hidden Markov model (HMM) that uses factorization of state transition probabilities to reduce...
Stjepan Rajko, Gang Qian, Todd Ingalls, Jodi James
ICPR
2010
IEEE
14 years 11 months ago
Audio-Visual Classification and Fusion of Spontaneous Affective Data in Likelihood Space
This paper focuses on audio-visual (using facial expression, shoulder and audio cues) classification of spontaneous affect, utilising generative models for classification (i) in t...
Mihalis A. Nicolaou, Hatice Gunes, Maja Pantic