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107
Voted
ICPR
2008
IEEE
15 years 9 months ago
Embedding HMM's-based models in a Euclidean space: The topological hidden Markov models
One of the major limitations of HMM-based models is the inability to cope with topology: When applied to a visible observation (VO) sequence, HMM-based techniques have difficulty ...
Djamel Bouchaffra
131
Voted
ICCV
2003
IEEE
16 years 4 months ago
Recognition of Group Activities using Dynamic Probabilistic Networks
Dynamic Probabilistic Networks (DPNs) are exploited for modelling the temporal relationships among a set of different object temporal events in the scene for a coherent and robust...
Shaogang Gong, Tao Xiang
NIPS
2004
15 years 4 months ago
Conditional Models of Identity Uncertainty with Application to Noun Coreference
Coreference analysis, also known as record linkage or identity uncertainty, is a difficult and important problem in natural language processing, databases, citation matching and m...
Andrew McCallum, Ben Wellner
DSOM
2009
Springer
15 years 9 months ago
Hidden Markov Model Modeling of SSH Brute-Force Attacks
Abstract. Nowadays, network load is constantly increasing and high-speed infrastructures (1-10Gbps) are becoming increasingly common. In this context, flow-based intrusion detecti...
Anna Sperotto, Ramin Sadre, Pieter-Tjerk de Boer, ...
117
Voted
ICCV
2001
IEEE
16 years 4 months ago
Topology Free Hidden Markov Models: Application to Background Modeling
Hidden Markov Models (HMMs) are increasingly being used in computer vision for applications such as: gesture analysis, action recognition from video, and illumination modeling. Th...
Bjoern Stenger, Visvanathan Ramesh, Nikos Paragios...