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» Generating from a Deep Structure
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ICASSP
2011
IEEE
12 years 9 months ago
Deep Belief Networks using discriminative features for phone recognition
Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...
INFOCOM
2012
IEEE
11 years 7 months ago
FlowSifter: A counting automata approach to layer 7 field extraction for deep flow inspection
Abstract—In this paper, we introduce FlowSifter, a systematic framework for online application protocol field extraction. FlowSifter introduces a new grammar model Counting Regu...
Chad R. Meiners, Eric Norige, Alex X. Liu, Eric To...
ICASSP
2011
IEEE
12 years 9 months ago
An atlas-based deep brain structure segmentation method: from coarse positioning to fine shaping
Segmentation of deep brain structures is a challenging task for MRI images due to blurry structure boundaries, small object size and irregular shapes. In this paper, we present a ...
Yishan Luo, Albert C. S. Chung
ICSR
2000
Springer
13 years 8 months ago
A New Control Structure for Transformation-Based Generators
A serious problem of most transformation-based generators is that they are trying to achieve three mutually antagonistic goals simultaneously: 1) deeply factored operators and oper...
Ted J. Biggerstaff
COLING
2002
13 years 5 months ago
From Shallow to Deep Parsing Using Constraint Satisfaction
We present in this paper a technique allowing to choose the parsing granularity within the same approach relying on a constraint-based formalism. Its main advantage lies in the fa...
Jean-Marie Balfourier, Philippe Blache, Tristan va...