Results 31 to 40 of about 4,196 (185)
Recognition of Planar Objects Using Multiresolution Analysis
EURASIP Journal on Advances in Signal Processing, 2007 By using affine-invariant shape descriptors, it is possible to recognize an unknown planar object from an image taken from an arbitrary view when standard view images of candidate objects exist in a database.
Ayşın Ertüzün +1 more
doaj +2 more sources
Local appearance-based face recognition using adaptive directional wavelet transform
Journal of King Saud University: Computer and Information Sciences, 2019 The latest research has shown that adaptive directional wavelet transform can constitute edges and textures in images efficiently due to the adaptive directional selectivity.
Mohd. Abdul Muqeet, Raghunath S. Holambe
doaj +1 more source
Nonlinear Engineering, 2018 Mathematical model for an adiabatic tubular chemical reactor which processes an irreversible exothermic chemical reaction has been considered. For steady state solution for an adiabatic tubular chemical reactor, the model can be reduced to ordinary ...
Sahu P. K., Ranjan A. K., Saha Ray S.
doaj +1 more source
A Quantitative Analysis of an EEG Epileptic Record Based on MultiresolutionWavelet Coefficients
Entropy, 2014 The characterization of the dynamics associated with electroencephalogram (EEG) signal combining an orthogonal discrete wavelet transform analysis with quantifiers originated from information theory is reviewed.
Mariel Rosenblatt +4 more
doaj +1 more source
Some generalized method for constructing nonseparable compactly supported wavelets in L^{2}(R^{2}) [PDF]
Opuscula Mathematica, 2013 In this paper we show some construction of nonseparable compactly supported bivariate wavelets. We deal with the dilation matrix \(A = \tiny{\left[\begin{matrix}0 & 2 \cr 1 & 0 \cr \end{matrix} \right]}\) and some three-row coefficient mask; that is a ...
Wojciech Banaś
doaj +1 more source
Combining Deep Learning and Multiresolution Analysis for Stock Market Forecasting
IEEE Access, 2021 Due to its complexity, financial time-series forecasting is regarded as one of the most challenging problems. During the past two decades, nonlinear modeling techniques, such as artificial neural networks, were commonly employed to solve a variety of ...
Khaled A. Althelaya +2 more
doaj +1 more source
Machine‐Learning‐Assisted Onset‐Time Determination in Transient Luminescence Thermometry
Advanced Intelligent Discovery, EarlyView.Artificial neural networks enable autonomous extraction of onset times from transient heating curves in luminescence thermometry. Using Ln3+‐doped upconverting nanoparticles as luminescent thermometers, we combine experimental transients with physically motivated synthetic curves to enhance data diversity and improve generalization.
David J. Sousa +3 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source
Deep Underground Science and Engineering, EarlyView.The flowchart illustrates rock specimen testing, vibration signal acquisition, and feature extraction with Gaborlet and sparse filtering for classification. Abstract Traditional lithology identification methods mainly rely on core sampling and well‐logging data.
Jian Hao +5 more
wiley +1 more source
Information, 2021 Stock movement prediction is important in the financial world because investors want to observe trends in stock prices before making investment decisions. However, given the non-linear non-stationary financial time series characteristics of stock prices,
Lifang Peng, Kefu Chen, Ning Li
doaj +1 more source