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ICML
2005
IEEE
14 years 8 months ago
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
NIPS
2007
13 years 8 months ago
Learning Visual Attributes
We present a probabilistic generative model of visual attributes, together with an efficient learning algorithm. Attributes are visual qualities of objects, such as ‘red’, ...
Vittorio Ferrari, Andrew Zisserman
WAPCV
2007
Springer
14 years 1 months ago
Language Label Learning for Visual Concepts Discovered from Video Sequences
Computational models of grounded language learning have been based on the premise that words and concepts are learned simultaneously. Given the mounting cognitive evidence for conc...
Prithwijit Guha, Amitabha Mukerjee
CLEIEJ
2002
192views more  CLEIEJ 2002»
13 years 7 months ago
Automatic ObjectPascal Code Generation from Catalysis Specifications
This paper presents a Component-based Framework Development Process, of the Cardiology Domain. The Framework, called FrameCardio, was developed in 4 steps: 1Problem Domain Definit...
João Luís Cardoso de Moraes, Ant&oci...
TMI
2010
208views more  TMI 2010»
13 years 2 months ago
Patient-Specific Modeling and Quantification of the Aortic and Mitral Valves From 4-D Cardiac CT and TEE
As decisions in cardiology increasingly rely on non-invasive methods, fast and precise image processing tools have become a crucial component of the analysis workflow. To the best ...
Razvan Ioan Ionasec, Ingmar Voigt, Bogdan Georgesc...