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ICPR
2002
IEEE
14 years 7 months ago
Robust Appearance-Based Object Recognition Using a Fully Connected Markov Random Field
This paper presents a new kernel method for appearance-based object recognition, highly robust to noise and occlusion. It consists of a fully connected Markov Random Field that in...
Barbara Caputo, Sahla Bouattour, Heinrich Niemann
ICML
2004
IEEE
14 years 7 months ago
Kernel conditional random fields: representation and clique selection
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
John D. Lafferty, Xiaojin Zhu, Yan Liu
EMMCVPR
1999
Springer
13 years 11 months ago
Auxiliary Variables for Markov Random Fields with Higher Order Interactions
Markov Random Fields are widely used in many image processing applications. Recently the shortcomings of some of the simpler forms of these models have become apparent, and models ...
Robin D. Morris
EMNLP
2010
13 years 4 months ago
Better Punctuation Prediction with Dynamic Conditional Random Fields
This paper focuses on the task of inserting punctuation symbols into transcribed conversational speech texts, without relying on prosodic cues. We investigate limitations associat...
Wei Lu, Hwee Tou Ng
ICPR
2006
IEEE
14 years 7 months ago
Type-2 Fuzzy Markov Random Fields to Handwritten Character Recognition
This paper integrates Markov random fields (MRFs) with type-2 fuzzy sets (T2 FSs) referred to as T2 FMRFs, which can handle the fuzziness of the labeling space as well as the rand...
Jia Zeng, Zhi-Qiang Liu