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ICASSP
2011
IEEE
14 years 10 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...
DSS
2011
14 years 10 months ago
Estimating the effect of word of mouth on churn and cross-buying in the mobile phone market with Markov logic networks
Abstract: Much has been written about word of mouth and customer behavior. Telephone call detail records provide a novel way to understand the strength of the relationship between ...
Torsten Dierkes, Martin Bichler, Ramayya Krishnan
CVPR
2012
IEEE
13 years 9 months ago
Top-down and bottom-up cues for scene text recognition
Scene text recognition has gained significant attention from the computer vision community in recent years. Recognizing such text is a challenging problem, even more so than the ...
Anand Mishra, Karteek Alahari, C. V. Jawahar
TVCG
2012
191views Hardware» more  TVCG 2012»
13 years 9 months ago
Live Speech Driven Head-and-Eye Motion Generators
—This paper describes a fully automated framework to generate realistic head motion, eye gaze, and eyelid motion simultaneously based on live (or recorded) speech input. Its cent...
Binh Huy Le, Xiaohan Ma, Zhigang Deng
BMCBI
2008
129views more  BMCBI 2008»
15 years 7 months ago
A unified approach to false discovery rate estimation
Background: False discovery rate (FDR) methods play an important role in analyzing highdimensional data. There are two types of FDR, tail area-based FDR and local FDR, as well as ...
Korbinian Strimmer