Results 21 to 30 of about 7,040 (158)
KPCA denoising and the pre-image problem revisited
Digital Signal Processing, 2008 Kernel principal component analysis (KPCA) is widely used in classification, feature extraction and denoising applications. In the latter it is unavoidable to deal with the pre-image problem which constitutes the most complex step in the whole processing chain.
Ana R. Teixeira +3 more
openaire +2 more sources
Age Sensitivity of Face Recognition Algorithms [PDF]
, 2013 This paper investigates the performance degradation of facial recognition systems due to the influence of age. A comparative analysis of verification performance is conducted for four subspace projection techniques combined with four different distance ...
Deravi, Farzin +2 more
core +1 more source
Robust PCA as Bilinear Decomposition with Outlier-Sparsity Regularization [PDF]
, 2011 Principal component analysis (PCA) is widely used for dimensionality reduction, with well-documented merits in various applications involving high-dimensional data, including computer vision, preference measurement, and bioinformatics.
Giannakis, Georgios B., Mateos, Gonzalo
core +1 more source
An Evaluation of Popular Copy-Move Forgery Detection Approaches
, 2012 A copy-move forgery is created by copying and pasting content within the same image, and potentially post-processing it. In recent years, the detection of copy-move forgeries has become one of the most actively researched topics in blind image forensics.
Angelopoulou, Elli +4 more
core +1 more source
Ages and Masses of 0.64 million Red Giant Branch stars from the LAMOST Galactic Spectroscopic Survey
, 2019 We present a catalog of stellar age and mass estimates for a sample of 640\,986 red giant branch (RGB) stars of the Galactic disk from the LAMOST Galactic Spectroscopic Survey (DR4).
Bi, S. +16 more
core +1 more source
Distribution network planning based on double deep Q‐network with self‐adjusting parameters
Energy Conversion and Economics, Volume 7, Issue 2, Page 105-126, April 2026.Abstract To address the challenge of low adaptability in distribution network planning caused by significant regional differences in electricity consumption, this paper proposes a distribution network planning method based on a self‐adjusting parameter double deep Q‐network (SAP‐DDQN).
Xingquan Ji +6 more
wiley +1 more source
The Promise of Low‐Cost Metal‐Oxide Semiconductor Gas Sensors for Precision Agriculture
Advanced Sensor Research, Volume 5, Issue 3, March 2026.Low‐cost MOS (metal‐oxide semiconductor) gas sensors are redefining smart farming. This review explores their role across soil monitoring, crop health assessment, and post‐harvest management. By addressing challenges of selectivity, signal drift, and data fusion, this work envisions MOS gas sensors as pivotal tools for intelligent, data‐driven, and ...
Ali Ahmad +5 more
wiley +1 more source
Advanced Intelligent Systems, Volume 8, Issue 3, March 2026.Adaptive multi‐indicator contrastive predictive coding is introduced as a self‐supervised pretraining framework for multivariate EHR time series. An adaptive sliding‐window algorithm and 2D convolutional neural network encoder capture localized temporal patterns and global indicator dependencies, enabling label‐efficient disease prediction that ...
Hongxu Yuan +3 more
wiley +1 more source
Clustering via kernel decomposition [PDF]
, 2006 Spectral clustering methods were proposed recently which rely on the eigenvalue decomposition of an affinity matrix. In this letter, the affinity matrix is created from the elements of a nonparametric density estimator and then decomposed to obtain ...
Girolami, M. +2 more
core +2 more sources
Speaker Recognition Based on KPCA and KFCM [PDF]
Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering, 2015 Speaker recognition system can identify a certain person using speech analysis. Recent advances in speech processing techniques improve the recognition rate. In this paper, an efficient speaker recognition system is proposed. Firstly, a KPCA-based feature selection approach is adopted to get the efficiently reduced dimension of feature vectors and ...
Yuanyuan Zhang, Jian Wang
openaire +1 more source