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» A Bootstrap Method for Training an Accurate Audio Segmenter
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ECCV
2010
Springer
13 years 8 months ago
Semantic Segmentation of Urban Scenes Using Dense Depth Maps
In this paper we present a framework for semantic scene parsing and object recognition based on dense depth maps. Five viewindependent 3D features that vary with object class are e...
Chenxi Zhang, Liang Wang, Ruigang Yang
BMCBI
2010
152views more  BMCBI 2010»
13 years 7 months ago
Comparative study of three commonly used continuous deterministic methods for modeling gene regulation networks
Background: A gene-regulatory network (GRN) refers to DNA segments that interact through their RNA and protein products and thereby govern the rates at which genes are transcribed...
Martin T. Swain, Johannes J. Mandel, Werner Dubitz...
NLPRS
2001
Springer
13 years 11 months ago
A Hierarchical EM Approach to Word Segmentation
We propose a simple two-level hierarchical probability model for unsupervised word segmentation. By treating words as strings composed of morphemes/phonemes which are themselves c...
Fuchun Peng, Dale Schuurmans
ICMLA
2008
13 years 8 months ago
Highly Scalable SVM Modeling with Random Granulation for Spam Sender Detection
Spam sender detection based on email subject data is a complex large-scale text mining task. The dataset consists of email subject lines and the corresponding IP address of the em...
Yuchun Tang, Yuanchen He, Sven Krasser
ICPR
2006
IEEE
14 years 8 months ago
Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning
It is possible to broadly characterize two approaches to probabilistic modeling in terms of generative and discriminative methods. Provided with sufficient training data the discr...
B. Michael Kelm, Chris Pal, Andrew McCallum