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ICASSP
2011
IEEE
12 years 11 months ago
Beyond bag of words: Combining generative and discriminative models for natural scene categorization
This paper proposes a simple yet new and effective framework by combining generative model and discriminative model for natural scene categorization. A state-of-the-art approach f...
Zhen Li, Kim-Hui Yap, Xiao-Ming Chen
CVPR
2008
IEEE
14 years 9 months ago
Combining appearance models and Markov Random Fields for category level object segmentation
Object models based on bag-of-words representations can achieve state-of-the-art performance for image classification and object localization tasks. However, as they consider obje...
Diane Larlus, Frédéric Jurie
BMVC
2001
13 years 10 months ago
Combining 3D Deformable Models and Level Set Methods for the Segmentation of Abdominal Aortic Aneurysms
In this paper we present a system that combines the benefits of 3D deformable models and level set methods for medical volume segmentation. Our 3D deformable model is a very comp...
Derek R. Magee, Andrew J. Bulpitt, Elizabeth Berry
ACL
2012
11 years 10 months ago
Incremental Joint Approach to Word Segmentation, POS Tagging, and Dependency Parsing in Chinese
We propose the first joint model for word segmentation, POS tagging, and dependency parsing for Chinese. Based on an extension of the incremental joint model for POS tagging and ...
Jun Hatori, Takuya Matsuzaki, Yusuke Miyao, Jun-ic...
MCS
2005
Springer
14 years 1 months ago
A Probability Model for Combining Ranks
Mixed Group Ranks is a parametric method for combining rank based classiers that is eective for many-class problems. Its parametric structure combines qualities of voting methods...
Ofer Melnik, Yehuda Vardi, Cun-Hui Zhang