AIMC Topic: Wavelet Analysis

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An optimal brain tumor detection by convolutional neural network and Enhanced Sparrow Search Algorithm.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Precise and timely detection of brain tumor area has a very high effect on the selection of medical care, its success rate and following the disease process during treatment. Existing algorithms for brain tumor diagnosis have problems in terms of bet...

Assessing the signal quality of electrocardiograms from varied acquisition sources: A generic machine learning pipeline for model generation.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: Long-term electrocardiogram monitoring comes at the expense of signal quality. During unconstrained movements, the electrocardiogram is often corrupted by motion artefacts, which can lead to inaccurate physiological informat...

Mitigation of ocular artifacts for EEG signal using improved earth worm optimization-based neural network and lifting wavelet transform.

Computer methods in biomechanics and biomedical engineering
An Electroencephalogram (EEG) is often tarnished by various categories of artifacts. Numerous efforts have been taken to improve its quality by eliminating the artifacts. The EEG involves the biological artifacts (ocular artifacts, ECG and EMG artifa...

A Novel Method for Sleep-Stage Classification Based on Sonification of Sleep Electroencephalogram Signals Using Wavelet Transform and Recurrent Neural Network.

European neurology
INTRODUCTION: Visual sleep-stage scoring is a time-consuming technique that cannot extract the nonlinear characteristics of electroencephalogram (EEG). This article presents a novel method for sleep-stage differentiation based on sonification of slee...

Classification of aortic stenosis using conventional machine learning and deep learning methods based on multi-dimensional cardio-mechanical signals.

Scientific reports
This paper introduces a study on the classification of aortic stenosis (AS) based on cardio-mechanical signals collected using non-invasive wearable inertial sensors. Measurements were taken from 21 AS patients and 13 non-AS subjects. A feature analy...

Research on a Dynamic Algorithm for Cow Weighing Based on an SVM and Empirical Wavelet Transform.

Sensors (Basel, Switzerland)
Weight is an important indicator of the growth and development of dairy cows. The traditional static weighing methods require considerable human and financial resources, and the existing dynamic weighing algorithms do not consider the influence of th...

Spectral-Spatial Features Integrated Convolution Neural Network for Breast Cancer Classification.

Sensors (Basel, Switzerland)
Cancer identification and classification from histopathological images of the breast depends greatly on experts, and computer-aided diagnosis can play an important role in disagreement of experts. This automatic process has increased the accuracy of ...

A combined HMM-PCNN model in the contourlet domain for image data compression.

PloS one
Multiscale geometric analysis (MGA) is not only characterized by multi-resolution, time-frequency localization, multidirectionality and anisotropy, but also outdoes the limitations of wavelet transform in representing high-dimensional singular data s...

Image Target Recognition via Mixed Feature-Based Joint Sparse Representation.

Computational intelligence and neuroscience
An image target recognition approach based on mixed features and adaptive weighted joint sparse representation is proposed in this paper. This method is robust to the illumination variation, deformation, and rotation of the target image. It is a data...

Classification of heart sounds based on the combination of the modified frequency wavelet transform and convolutional neural network.

Medical & biological engineering & computing
We purpose a novel method that combines modified frequency slice wavelet transform (MFSWT) and convolutional neural network (CNN) for classifying normal and abnormal heart sounds. A hidden Markov model is used to find the position of each cardiac cyc...