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Wavelet Analysis

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Interpretation of Electrocardiogram Heartbeat by CNN and GRU.

Computational and mathematical methods in medicine
The diagnosis of electrocardiogram (ECG) is extremely onerous and inefficient, so it is necessary to use a computer-aided diagnosis of ECG signals. However, it is still a challenging problem to design high-accuracy ECG algorithms suitable for the med...

Forecasting air pollutant concentration using a novel spatiotemporal deep learning model based on clustering, feature selection and empirical wavelet transform.

The Science of the total environment
Accurate forecasting of air pollutant concentration is of great importance since it is an essential part of the early warning system. However, it still remains a challenge due to the limited information of emission source and high uncertainties of th...

WaveCNet: Wavelet Integrated CNNs to Suppress Aliasing Effect for Noise-Robust Image Classification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Though widely used in image classification, convolutional neural networks (CNNs) are prone to noise interruptions, i.e. the CNN output can be drastically changed by small image noise. To improve the noise robustness, we try to integrate CNNs with wav...

Investigation of spectrophotometric simultaneous absorption of Salmeterol and Fluticasone in Seroflo spray by continuous wavelet transform and radial basis function neural network methods.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this research, the simultaneous absorption of Salmeterol (SAL) and Fluticasone (FLU) in Seroflo spray was investigated using a spectrophotometric device via employing continuous wavelet transform (CWT) and radial basis function neural network (RBF...

CNN-Based Classifier as an Offline Trigger for the CREDO Experiment.

Sensors (Basel, Switzerland)
Gamification is known to enhance users' participation in education and research projects that follow the citizen science paradigm. The Cosmic Ray Extremely Distributed Observatory (CREDO) experiment is designed for the large-scale study of various ra...

A semi-analytical solution and AI-based reconstruction algorithms for magnetic particle tracking.

PloS one
Magnetic particle tracking is a recently developed technology that can measure the translation and rotation of a particle in an opaque environment like a turbidity flow and fluidized-bed flow. The trajectory reconstruction usually relies on numerical...

Texture Image Classification Method of Porcelain Fragments Based on Convolutional Neural Network.

Computational intelligence and neuroscience
The texture image decomposition of porcelain fragments based on convolutional neural network is a functional algorithm based on energy minimization. It maps the image to a suitable space and can effectively decompose the image structure, texture, and...

Obstructive sleep apnea prediction from electrocardiogram scalograms and spectrograms using convolutional neural networks.

Physiological measurement
In this study, we conducted a comparative analysis of deep convolutional neural network (CNN) models in predicting obstructive sleep apnea (OSA) using electrocardiograms. Unlike other studies in the literature, this study automatically extracts time-...

A spectrogram image based intelligent technique for automatic detection of autism spectrum disorder from EEG.

PloS one
Autism spectrum disorder (ASD) is a developmental disability characterized by persistent impairments in social interaction, speech and nonverbal communication, and restricted or repetitive behaviors. Currently Electroencephalography (EEG) is the most...

Multispectral co-occurrence of wavelet coefficients for malignancy assessment of brain tumors.

PloS one
Brain tumor is not most common, but truculent type of cancer. Therefore, correct prediction of its aggressiveness nature at an early stage would influence the treatment strategy. Although several diagnostic methods based on different modalities exist...