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MPCA: Multilinear Principal Component Analysis of Tensor Objects
TLDR
It is shown that even without a fully optimized design, an MPCA-based gait recognition module achieves highly competitive performance and compares favorably to the state-of-the-art gait recognizers. Expand
Color Image Processing and Applications
This book claims to fill a niche in the provision of textbooks devoted to image processing by being devoted to colour aspects. It is aimed at researchers and practitioners working in the area ofExpand
Face recognition using LDA-based algorithms
TLDR
A new algorithm is proposed that deals with both of the shortcomings in an efficient and cost effective manner of traditional linear discriminant analysis methods for face recognition systems. Expand
Face recognition using kernel direct discriminant analysis algorithms
TLDR
This paper proposes a kernel machine-based discriminant analysis method, which deals with the nonlinearity of the face patterns' distribution and effectively solves the so-called "small sample size" (SSS) problem, which exists in most FR tasks. Expand
Analysis of Human Electrocardiogram for Biometric Recognition
TLDR
A fiducial-detection-based framework that incorporates analytic and appearance attributes is first introduced and a new approach based on autocorrelation (AC) in conjunction with discrete cosine transform (DCT) is proposed. Expand
Kernel-Based Positioning in Wireless Local Area Networks
TLDR
It is shown that, due to the variability of RSS features over space, a spatially localized positioning method leads to improved positioning results and a kernelized distance calculation algorithm for comparing RSS observations to RSS training records is presented. Expand
Regularization studies of linear discriminant analysis in small sample size scenarios with application to face recognition
TLDR
A new LDA method is proposed that attempts to address the SSS problem using a regularized Fisher's separability criterion and a scheme of expanding the representational capacity of face database is introduced to overcome the limitation that the LDA-based algorithms require at least two samples per class available for learning. Expand
Regularized Common Spatial Pattern With Aggregation for EEG Classification in Small-Sample Setting
TLDR
A regularized CSP (R-CSP) algorithm is proposed, where the covariance-matrix estimation is regularized by two parameters to lower the estimation variance while reducing the estimation bias. Expand
Color filter arrays: design and performance analysis
TLDR
The design of color filter arrays (CFAs) used in the consumer-grade digital camera are described, and their influence on the performance of the demosaicking process is analyzed. Expand
COVID-CAPS: A capsule network-based framework for identification of COVID-19 cases from X-ray images
TLDR
Results based on a dataset of X-ray images show that COVID-CAPS has advantage over previous CNN-based models, being capable of handling small datasets, which is of significant importance due to sudden and rapid emergence of CO VID-19. Expand
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