Results 251 to 260 of about 62,563 (288)

Pedestrian detection by PCA-based mixed HOG-LBP features

Proceedings of the 4th International Conference on Internet Multimedia Computing and Service, 2012
As the basic method of feature extraction, HOG and LBP are paid much attention in the field of pedestrian detection. But the HOG features are too narrow and complex, so we simplify the HOG from the two perspectives. After that, PCA is used to reduce the dimensions of simplified HOG features and LBP features and then combine the two features after the ...
Ren-wu Sun, Ting Rui, Jinlin Zhang, You Zhou 0002   +3 more
openaire   +1 more source

Research on mixed PCA/ICA for SAR image feature extraction

2008 9th International Conference on Signal Processing, 2008
The differences between Principal Component Analysis (PCA) and Independent Component Analysis (ICA) for feature extraction are analyzed theoretically and experimentally, and a mixed PCA/ICA transform is developed for Synthetic Aperture Radar image feature extraction. This method combines the subspace produced by PCA and the subspace generated by ICA to
null Xiaoguang Lu, null Ping Han, null Renbiao Wu   +2 more
openaire   +1 more source

Mixed PCA/ICA spectral/spatial compression for hyperspectral imagery

SPIE Proceedings, 2005
Principal components analysis (PCA) has been widely used in many applications, particularly, data compression. Independent component analysis (ICA) has been also developed for blind source separation along with many other applications such as channel equalization, speech processing.
Jing Wang, Chein-I Chang
openaire   +1 more source

PCA application to frequency reduction for fault diagnosis in analog and mixed electronic circuit

Proceedings of 2010 IEEE International Symposium on Circuits and Systems, 2010
This paper is focused on the diagnosis of analog and mixed electronic circuit in frequency domain. A multi tone signal excites a circuit under test in order to detect and locate a single fault. The input signal consists of a number of frequencies which are selected by Principal Component Analysis (PCA) algorithm.
Damian Grzechca, Jerzy Rutkowski, Tomasz Golonek   +2 more
openaire   +1 more source

Testing and selecting mixed data type DEA scenarios with PCA post-processing

2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC), 2017
Data Envelopment Analysis (DEA) with a large amount of variables and little DMUs is problematic. Such a configuration with high variable dimensionality yields too much 100 % efficient DMUs, hence making results invaluable. In this paper a new method is provided, which applies Principal Component Analysis (PCA) as a post-processing tool, to test and ...
Niels P. Theunissen, Scott W. Cunningham
openaire   +1 more source

Quality evaluation of mixed brewed perries based on PCA and sensory evaluation

Frontiers of Agriculture in China, 2011
In order to improve the sensory quality of Yali perry and choose fruits specially suitable for mixed fermentation with Yali pear, 11 kinds of fruits were selected and contrasted, including hawthorn, kiwifruit, Kyoho grape, Brown plum, Fuji apple, Nanguo pear, Dongzao jujube, Mopan persimmon, Korla pear, and Chi pear.
Yanhui Wang, Yuan Liu, Yuxing Zhang, Zhanyang Xu   +3 more
openaire   +1 more source

An investigation on dimensional accuracy and surface topography in powder mixed WEDM using RSM and GRA-PCA

Materials Today: Proceedings, 2021
Abstract The dimensional accuracy in terms of corner error is the critical concern in the wire EDM (WEDM) process where the minor error is not acceptable in the advance manufacturing industry. Superfine Surface topography has also similar importance for application to avoid further machining and lower machining cost.
Sadananda Chakraborty, Souren Mitra, Dipankar Bose   +2 more
openaire   +1 more source

Kernel PCA Based Estimation of the Mixing Matrix in Linear Instantaneous Mixtures of Sparse Sources

2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006
Source sparsity based methods have become a common approach to blind source separation (BSS) problems, especially in the underdetermined case (more sources than sensors). If the sources are not sparse in the time-domain, in most cases, they can be mapped to a transformed domain (e.g., wavelets, time-frequency, Fourier) in which this assumption is ...
Frédéric Desobry, Cédric Févotte
openaire   +1 more source

Novel one-part geopolymer concrete mix design using hybrid Taguchi GRA-PCA optimization approach

Structures
Satadru Das Adhikary, Prabir Kumar Sarker   +1 more
exaly   +2 more sources

A Mixed Algorithm of PCA and LDA for Fault Diagnosis of Induction Motor

2007
In this paper, we propose a feature extraction method and fusion algorithm which is constructed by PCA and LDA to detect a fault state of the induction motor that is applied over the whole field of a industry. After yielding a feature vector from current signal which is measured by an experiment using PCA and LDA, we use the reference data to produce ...
Wook Je Park, Sang H. Lee, Won Kyung Joo, Jung Il Song   +3 more
openaire   +1 more source