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ICML
2010
IEEE
13 years 6 months ago
A Conditional Random Field for Multiple-Instance Learning
We present MI-CRF, a conditional random field (CRF) model for multiple instance learning (MIL). MI-CRF models bags as nodes in a CRF with instances as their states. It combines di...
Thomas Deselaers, Vittorio Ferrari
RIAO
2007
13 years 7 months ago
Discriminative Fields for Modeling Semantic Concepts in Video
According to some current thinking, a very large number of semantic concepts could provide researcher a novel way to characterize video and be utilized for video retrieval and und...
Ming-yu Chen, Alexander G. Hauptmann
EMMCVPR
2005
Springer
13 years 11 months ago
Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study
Abstract. Estimation of parameters of random field models from labeled training data is crucial for their good performance in many image analysis applications. In this paper, we p...
Sanjiv Kumar, Jonas August, Martial Hebert
ICIP
2000
IEEE
14 years 7 months ago
Definition of a Spatial Entropy and its Use for Texture Discrimination
This paper presents a new definition of a spatial entropy mainly based on the Markov Random Field (MRF) properties. Starting with the study of the entropy proposed in [1] for the ...
Florence Tupin, Henri Maître, Marc Sigelle
ICASSP
2008
IEEE
14 years 3 days ago
Maximum conditional likelihood linear regression and maximum a posteriori for hidden conditional random fields speaker adaptatio
This paper shows how to improve Hidden Conditional Random Fields (HCRFs) for phone classification by applying various speaker adaptation techniques. These include Maximum A Poste...
Yun-Hsuan Sung, Constantinos Boulis, Daniel Jurafs...