Results 101 to 110 of about 7,040 (158)

Fall Detection Based on KPCA and 3D KPCA

2016 IEEE Trustcom/BigDataSE/ISPA, 2016
Falls in elderly remain a very important public health care issue. The wearable devices based on tri-axial accelerator proves to be an effective tool for fall detection in the recent years. In this paper, we propose an approach to distinguish falls and normal activities of daily living (ADL).
Hui Wang, Xiaohe Chen, Xinjian Chen 0001, Peilin Zang, Yunqing Liu, Lirong Wang   +5 more
openaire   +1 more source

Adaptive KPCA Modeling of Nonlinear Systems

IEEE Transactions on Signal Processing, 2015
This paper proposes an adaptive algorithm for kernel principal component analysis (KPCA). Compared to existing work: i) the proposed algorithm does not rely on assumptions, ii) combines the up- and downdating step to become a single operation, iii) the adaptation of the eigendecompsition can, computationally, reduce to $O(N)$ and iv) the proposed ...
Zhe Li, Uwe Kruger 0001, Lei Xie 0007, Ali Almansoori, Hongye Su   +4 more
openaire   +1 more source

Face Hallucination Through KPCA

2009 2nd International Congress on Image and Signal Processing, 2009
This paper demonstrates how Kernel Principal Component Analysis (KPCA) can be used for face hallucination. Different with other KPCA-based methods, KPCA in this paper handles samples from two subspaces, namely the high- and low- resolution image spaces.
Yan Liang, Jian-Huang Lai, Yao-Xian Zou, Wei Zheng, Pong C. Yuen   +4 more
openaire   +1 more source

Gender identification in face images using KPCA

2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 2009
The data in face images are distributed in a complex manner due to the variation of light intensity, facial expression and pose. In this paper the Kernel Principal Component Analysis (KPCA) is used to extract the feature set of male and female faces.
S. Aji, T. Jayanthi, M. Ramachandra Kaimal   +2 more
openaire   +1 more source

Kernel optimisation for KPCA based on Gaussianity estimation

International Journal of Bio-Inspired Computation, 2014
Kernel-based principle component analysis KPCA is an effective feature extraction method. It extends PCA to nonlinear cases using kernel trick. The performance of KPCA relies on the pre-selected parameter of kernel function. In this paper, we propose a kernel parameter optimisation method by using principle component subspace-based Gaussianity ...
Qi Kang, Kang Wang, BingYao Huang, Jing An 0001   +3 more
openaire   +1 more source

An adaptive KPCA approach for detecting LDoS attack

International Journal of Communication Systems, 2015
SummaryLow‐rate denial‐of‐service (LDoS) attack sends out attack packets at low‐average rate of traffic flow in short time. It is stealthier than traditional DoS attack, which makes detection of LDoS extremely difficult. In this paper, an adaptive kernel principal component analysis method is proposed for LDoS attack detection. The network traffic flow
Xiaoyu Zhang 0003, Zhijun Wu 0001, Jiusheng Chen, Meng Yue   +3 more
openaire   +1 more source

Learning KPCA for Face Recognition

2013
Kernel principal component analysis (KPCA) is an effective method for face recognition. However, the expression of its final solution needs to take advantage of all training examples, such that its run in real-world application with large scale training set is time-consuming.
Wangli Hao, Jianwu Li, Xiao Zhang
openaire   +1 more source

Sparse KPCA for Feature Extraction in Speech Recognition

Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2006
This paper presents an analysis of the applicability of sparse kernel principal component analysis (SKPCA) for feature extraction in speech recognition, as well as a proposed approach to make the SKPCA technique realizable for a large amount of training data, which is a usual context in speech recognition systems.
Amaro A. de Lima, Heiga Zen, Yoshihiko Nankaku, Keiichi Tokuda, Tadashi Kitamura, Fernando Gil Resende   +5 more
openaire   +1 more source

Personal Credit Assessment Based on KPCA and SVM

2012 Fifth International Conference on Business Intelligence and Financial Engineering, 2012
Personal credit assessment is carried out by setting up a mathematical model to count, calculate and analyze the personal credit data. At present personal credit assessment has already became a kind of worldwide industry. In this paper we combine kernel principal component analysis and support vector machine to propose a new mathematical model based on
Jing Wang, Yongsheng Zhou, Xinjian Du, Mingke He   +3 more
openaire   +1 more source

The transformer fault diagnosis combing KPCA with PNN

2014 International Joint Conference on Neural Networks (IJCNN), 2014
The probabilistic neural network (PNN) can detect the complex relationships and be used to develop its basis for the interpretation of dissolved gas-in-oil data that can identify the fault types. An efficient algorithm known as the kernel principle component analysis (KPCA) is applied to increase features in order to get higher detection accuracy. KPCA
Chenxi Dai, Zhigang Liu 0001, Yan Cui
openaire   +1 more source