Person re-identification by local maximal occurrence representation and metric learning
Person re-identification is an important technique towards automatic search of a person's
presence in a surveillance video. Two fundamental problems are critical for person re …
presence in a surveillance video. Two fundamental problems are critical for person re …
Classification of hyperspectral images with regularized linear discriminant analysis
TV Bandos, L Bruzzone… - IEEE Transactions on …, 2009 - ieeexplore.ieee.org
This paper analyzes the classification of hyperspectral remote sensing images with linear
discriminant analysis (LDA) in the presence of a small ratio between the number of training …
discriminant analysis (LDA) in the presence of a small ratio between the number of training …
The role of spectral resolution and classifier complexity in the analysis of hyperspectral images of forest areas
M Dalponte, L Bruzzone, L Vescovo… - Remote Sensing of …, 2009 - Elsevier
Remote sensing hyperspectral sensors are important and powerful instruments for
addressing classification problems in complex forest scenarios, as they allow one a detailed …
addressing classification problems in complex forest scenarios, as they allow one a detailed …
[PDF][PDF] Discriminant analysis for dimensionality reduction: An overview of recent developments
Many biometric applications such as face recognition involve data with a large number of
features [1–3]. Analysis of such data is challenging due to the curse-ofdimensionality [4, 5] …
features [1–3]. Analysis of such data is challenging due to the curse-ofdimensionality [4, 5] …
Heterogeneous face recognition from local structures of normalized appearance
Heterogeneous face images come from different lighting conditions or different imaging
devices, such as visible light (VIS) and near infrared (NIR) based. Because heterogeneous …
devices, such as visible light (VIS) and near infrared (NIR) based. Because heterogeneous …
[图书][B] Biometrics: theory, methods, and applications
NV Boulgouris, KN Plataniotis, E Micheli-Tzanakou - 2009 - books.google.com
Edited by a panel of experts, this book fills a gap in the existing literature by
comprehensively covering system, processing, and application aspects of biometrics, based …
comprehensively covering system, processing, and application aspects of biometrics, based …
Regularized linear discriminant analysis of EEG features in dementia patients
E Neto, F Biessmann, H Aurlien, H Nordby… - Frontiers in aging …, 2016 - frontiersin.org
The present study explores if EEG spectral parameters can discriminate between healthy
elderly controls (HC), Alzheimer's disease (AD) and vascular dementia (VaD) using. We …
elderly controls (HC), Alzheimer's disease (AD) and vascular dementia (VaD) using. We …
Modified linear discriminant analysis approaches for classification of high-dimensional microarray data
P Xu, GN Brock, RS Parrish - Computational Statistics & Data Analysis, 2009 - Elsevier
Linear discriminant analysis (LDA) is one of the most popular methods of classification. For
high-dimensional microarray data classification, due to the small number of samples and …
high-dimensional microarray data classification, due to the small number of samples and …
A comparative analysis of classifiers in emotion recognition through acoustic features
S Kuchibhotla, HD Vankayalapati, RS Vaddi… - International Journal of …, 2014 - Springer
The most popular features used in speech emotion recognition are prosody and spectral.
However the performance of the system degrades substantially, when these acoustic …
However the performance of the system degrades substantially, when these acoustic …
CP-CHARM: segmentation-free image classification made accessible
Background Automated classification using machine learning often relies on features
derived from segmenting individual objects, which can be difficult to automate. WND …
derived from segmenting individual objects, which can be difficult to automate. WND …