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» Neural Learning from Unbalanced Data Using Noise Modeling
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NPL
2006
85views more  NPL 2006»
13 years 5 months ago
A Neural Model for Context-dependent Sequence Learning
A novel neural network model is described that implements context-dependent learning of complex sequences. The model utilises leaky integrate-and-fire neurons to extract timing inf...
Luc Berthouze, Adriaan G. Tijsseling
IJCNN
2006
IEEE
13 years 11 months ago
Data Fusion for Outlier Detection through Pseudo-ROC Curves and Rank Distributions
— This paper proposes a novel method of fusing models for classification of unbalanced data. The unbalanced data contains a majority of healthy (negative) instances, and a minor...
Paul F. Evangelista, Mark J. Embrechts, Boleslaw K...
ICASSP
2011
IEEE
12 years 9 months ago
A non-negative approach to semi-supervised separation of speech from noise with the use of temporal dynamics
We present a semi-supervised source separation methodology to denoise speech by modeling speech as one source and noise as the other source. We model speech using the recently pro...
Gautham J. Mysore, Paris Smaragdis
ICPR
2008
IEEE
14 years 6 months ago
Extraction of shoe-print patterns from impression evidence using Conditional Random Fields
Impression evidence in the form of shoe-prints are commonly found in crime scenes. A critical step in automatic shoe-print identification is extraction of the shoe-print pattern. ...
Sargur N. Srihari, Veshnu Ramakrishnan
DICTA
2003
13 years 6 months ago
Learning Semantic Concepts from Visual Data Using Neural Networks
For content-based image retrieval techniques, query image is used to pick up and rank some relevant images from a database using some certain similarity metric. If semantic feature...
Xiaohang Ma, Dianhui Wang