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Linear Regression for Face Recognition
In this paper, we present a novel approach of face identification by formulating the pattern recognition problem in terms of linear regression. Using a fundamental concept that patterns from aExpand
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An Overview of Speaker Identification: Accuracy and Robustness Issues
This paper presents the main paradigms for speaker identification, and recent work on missing data methods to increase robustness. The feature extraction, speaker modeling and system classificationExpand
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Statistical Voice Activity Detection Using Low-Variance Spectrum Estimation and an Adaptive Threshold
Traditionally, voice activity detection algorithms are based on any combination of general speech properties such as temporal energy variations, periodicity, and spectrum. This paper describes aExpand
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Robust Regression for Face Recognition
In this paper we address the problem of illumination invariant face recognition. Using a fundamental concept that in general, patterns from a single object class lie on a linear subspace [2], weExpand
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Cost-Sensitive Learning of Deep Feature Representations From Imbalanced Data
Class imbalance is a common problem in the case of real-world object detection and classification tasks. Data of some classes are abundant, making them an overrepresented majority, and data of otherExpand
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Automatic Shadow Detection and Removal from a Single Image
We present a framework to automatically detect and remove shadows in real world scenes from a single image. Previous works on shadow detection put a lot of effort in designing shadow variant andExpand
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Sparse Representation for Speaker Identification
We address the closed-set problem of speaker identification by presenting a novel sparse representation classification algorithm. We propose to develop an over complete dictionary using the GMM meanExpand
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Automatic Feature Learning for Robust Shadow Detection
We present a practical framework to automatically detect shadows in real world scenes from a single photograph. Previous works on shadow detection put a lot of effort in designing shadow variant andExpand
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Modelling 1-D signals using Hermite basis functions
The paper discusses a method for estimating the Hermite coefficients of a discrete-time one-dimensional signal. To estimate the Hermite coefficients a solution based on Gaussian quadratures is used.Expand
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Convolutive blind signal separation with post-processing
A new subband based speech enhancement scheme is presented. It integrates spatial and temporal signal processing methods to enhance speech signals in a noisy environment. The approach makes use ofExpand
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