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Multi-mother wavelet neural network based on genetic algorithm and multiresoluion analysis for fast 3d mesh deformation
2019
IET Image Processing
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The current study presents a new 3D mesh deformation process using multi-mother wavelet neural network architecture, which relies on genetic algorithm and multiresolution analysis. ...
The main objective of the authors' proposed approach is that it prevents both the insufficiency and local minima by integrating the genetic algorithm; their wavelet network is used as an approximation ...
For 3D deformed object, we propose MMWNN-GA-MA to model and deform 3D meshes, the idea is to present a GA that makes it possible to decrease or to increase the dimension of the multi-mother wavelet library ...
doi:10.1049/iet-ipr.2019.0343
fatcat:7lvehtqnnfg5tiaxzoxmgxvod4
Curvelet Transform for Efficient Static Texture Classification and Image Fusion
2018
International Journal of Image Graphics and Signal Processing
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Thus wavelets are able represent graphical objects. The irregular shape and compact support of wavelets made them ideal for analyzing non-stationary signals. ...
Wavelet Transform (WT) has widely been used in signal processing. WT breaks a signal into its wavelets that are scaled and shifted versions of given signal. ...
Wavelet changes scale by scale is used in the CCT while Smith's CCT was based on strict affine parabolic scaling pertaining to a single mother wavelet. ...
doi:10.5815/ijigsp.2018.05.07
fatcat:j4zcoznb4jbo3ojywakravx34y
Multi-Level Haar Wavelet based Facial Expression Recognition using Logistic Regression
2017
Indian Journal of Science and Technology
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All logistic regression model is used for the classification. ...
The approach first segments most informative geometric components such as eye, mouth, eyebrows etc. using the Viola-Jones cascade object detector. Haar features of segmented components are extracted. ...
A general framework for local appearance based approach is depicted in Figure 1 . In this paper, we propose a novel approach using haar wavelets for facial expression classification. ...
doi:10.17485/ijst/2017/v10i9/108944
fatcat:viq3isznjnhsze4a6la3dxiusq
A CNN Deep Local and Global ASD Classification Approach with Continuous Wavelet Transform Using Task-Based FMRI
2021
Sensors
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A novel computer aided diagnosis (CAD) framework is proposed to classify 50 ASD and 50 typically developed toddlers with the adoption of CNN deep networks. ...
Developing objective computer aided technologies for ASD diagnosis with the utilization of brain imaging modalities and machine learning is one of main tracks in current studies to understand autism. ...
A multi-channel 2D CNN local model is developed for each area, fed with corresponding CWT scalograms. The final global classification decision is fused using majority voting approach. ...
doi:10.3390/s21175822
pmid:34502710
fatcat:nsmkeoojgfcfrlg553xgwpyvrm
Content-Based Image Retrieval and Feature Extraction: A Comprehensive Review
2019
Mathematical Problems in Engineering
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To search for a relevant image from an archive is a challenging research problem for computer vision research community. ...
We analyzed the main aspects of various image retrieval and image representation models from low-level feature extraction to recent semantic deep-learning approaches. ...
However, the feature dimensions are not higher than other approaches and require a high computational cost. ...
doi:10.1155/2019/9658350
fatcat:dncplhkm6vcrvfh3q7ifxkrdkq
A Review of Wavelet Analysis and Its Applications: Challenges and Opportunities
2022
IEEE Access
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Through the review, new research challenges and gaps have been clarified, which will serve as a guide for potential wavelet-based applications and new system designs. ...
The combination of wavelet theory and neural networks is one of the key points of the review. ...
Both orthogonal scaling functions and the corresponding mother wavelets are used and extended WNN to the multi-dimensional cases. ...
doi:10.1109/access.2022.3179517
fatcat:esfc4umo4vgzlbqa7lfxsl7e4m
COVID-19 Pneumonia Classification Based on NeuroWavelet Capsule Network
2022
Healthcare
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Therefore, we propose a novel method for the classification of COVID-19. Concretely, a novel neurowavelet capsule network is proposed for COVID-19 classification. ...
Our approach achieves an up-to-date performance that is useful for COVID-19 screening according to the experimental results. ...
A weakly supervised approach was proposed in [47] . This approach produced segmentation masks automatically. For classification, the mask and CT image are introduced into a 3D CNN. ...
doi:10.3390/healthcare10030422
pmid:35326900
pmcid:PMC8949056
fatcat:ih5dozzdircjrjqwid2zrill6a
Augmented CWT Features for Deep Learning-Based Indoor Localization Using WiFi RSSI Data
2021
Applied Sciences
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Therefore, new positioning solutions tailored for indoor environments need to be developed. In this paper, we propose a deep learning approach for indoor localization. ...
However, the performance of a deep learning system depends on the quality of the feature representation. ...
Figure 1 . 1 (a) A standard Morlet mother wavelet. (b) A standard Morse mother wavelet.
Figure 2 . 2 Figure 2. The general structure of the convolutional neural network considered. ...
doi:10.3390/app11041806
fatcat:7lcdk5gfqffp7m6pdzg2ntclhi
Quantification of ultrasonic texture intra-heterogeneity via volumetric stochastic modeling for tissue characterization
2015
Medical Image Analysis
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This paper proposes a locally adaptive 3D multi-resolution Nakagami-based fractal feature descriptor that extends Nakagami-based texture analysis to accommodate subtle speckle spatial frequency tissue ...
Using ultrasound radio-frequency datasets we found that after applying an adaptive fractal decomposition label transfer approach on top of the generated Nakagami voxels, tissue characterization results ...
The authors would like to thank the anonymous reviewers for their constructive comments and suggestions to improve the quality of the paper. ...
doi:10.1016/j.media.2014.12.004
pmid:25595523
pmcid:PMC4339203
fatcat:b7jhseyhardihpa3mz4q5mjrde
Deep-Learned Generators of Porosity Distributions Produced During Metal Additive Manufacturing
[article]
2022
arXiv
pre-print
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A framework is introduced that combines Generative Adversarial Networks with Mallat Scattering Transform-based autocorrelation methods to construct novel realizations of the individual pore geometries ...
Thus, controlling porosity is integral for creating effective parts. A precise understanding of the porosity distribution is crucial for accurately simulating potential fatigue and failure zones. ...
The moment of inertia tensor is first calculated from the 3D pore representation using the computed three-dimensional image moments. ...
arXiv:2205.05794v1
fatcat:zttsvoojwvfwpometgx5n6vlby
Robust Classification Technique for Hyperspectral Images Based on 3D-Discrete Wavelet Transform
2021
Remote Sensing
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Three-dimensional discrete wavelet transform (3D-DWT) has the advantage of extracting the spatial and spectral information simultaneously. ...
Decomposing an image into a set of spatial–spectral components is an important characteristic of 3D-DWT. It has motivated us to perform the proposed research work. ...
For a large class of signals, the wavelet transform offers sparse representation. ...
doi:10.3390/rs13071255
fatcat:aefwerueq5h7jaufdf74zowyum
A Review of Signal Processing Techniques for Ultrasonic Guided Wave Testing
2022
Metals
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Ultrasonic guided wave testing (UGWT) is a non-destructive testing (NDT) technique commonly used in structural health monitoring to perform wide-range inspection from a single point, thus reducing the ...
The purpose of this article is to give an overview of signal processing techniques used for filtering signals, isolating modes and identifying and localising defects in UGWT. ...
Author Year Technique Summary and Results
He C. [33] 2008 Multi-level discrete wavelet decomposition and single branch reconstruction The Daubechies wavelet of order 40 is used as the mother wavelet ...
doi:10.3390/met12060936
fatcat:qg4atwih45clphsugwp27mexsa
Real-Time Emotion Classification Using EEG Data Stream in E-Learning Contexts
2021
Sensors
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For this, we propose a real-time emotion classification system (RECS)-based Logistic Regression (LR) trained in an online fashion using the Stochastic Gradient Descent (SGD) algorithm. ...
However, these offline mode approaches are inappropriate for real-time emotion classification when the data are coming in a continuous stream and data can be seen to the model at once only. ...
In multi-dimensional space, each emotion can be placed as a continuous and coordinated point in 3D or 2D. ...
doi:10.3390/s21051589
pmid:33668757
pmcid:PMC7956809
fatcat:f4co4334nzh2fnl7grczuz7dkq
EEG Classification by factoring in Sensor Spatial Configuration
2021
IEEE Access
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A new approach is examined here for enhancing EEG classification performance using a novel model of data representation that leverages knowledge of spatial layout of EEG sensors. ...
image-like two-dimensional representation of the EEG channel locations. ...
We investigate two data representation models for classification -a 1-Dimensional (1D) Concatenated Data Representation (1D-CDR) model and a 2-Dimensional (2D) Interpolated Data Representation (2D-IDR) ...
doi:10.1109/access.2021.3054670
fatcat:vgfesjrw7va5pktaiiy5qn3i6a
A Novel Image Compression Algorithm for High Resolution 3D Reconstruction
2014
3D Research
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This research presents a novel algorithm to compress high-resolution images for accurate structured light 3D reconstruction. ...
The Compression Algorithm starts with a single level discrete wavelet transform (DWT) for decomposing an image into four sub-bands. ...
The LL 2 is transformed by using one-dimensional DCT for each 4 items of data (i.e. assume u = 0, v = 0 to converting two dimensional DCT into one dimensional DCT), and then truncate each value. ...
doi:10.1007/s13319-014-0007-6
fatcat:phyaqlao2fe65oy3567b6nb35e
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