AIMC Topic: Wavelet Analysis

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A Wavelet Transform-Based Neural Network Denoising Algorithm for Mobile Phonocardiography.

Sensors (Basel, Switzerland)
Cardiovascular pathologies cause 23.5% of human deaths, worldwide. An auto-diagnostic system monitoring heart activity, which can identify the early symptoms of cardiac illnesses, might reduce the death rate caused by these problems. Phonocardiograph...

Multifocus Image Fusion Using Wavelet-Domain-Based Deep CNN.

Computational intelligence and neuroscience
Multifocus image fusion is the merging of images of the same scene and having multiple different foci into one all-focus image. Most existing fusion algorithms extract high-frequency information by designing local filters and then adopt different fus...

Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In recent years, deep learning algorithms have become increasingly more prominent for their unparalleled ability to automatically learn discriminant features from large amounts of data. However, within the field of electromyography-based gesture reco...

Blind Noisy Image Quality Assessment Using Sub-Band Kurtosis.

IEEE transactions on cybernetics
Noise that afflicts natural images, regardless of the source, generally disturbs the perception of image quality by introducing a high-frequency random element that, when severe, can mask image content. Except at very low levels, where it may play a ...

A Lung Sound Category Recognition Method Based on Wavelet Decomposition and BP Neural Network.

International journal of biological sciences
In this paper, a method of characteristic extraction and recognition on lung sounds is given. Wavelet de-noised method is adopted to reduce noise of collected lung sounds and extract wavelet characteristic coefficients of the de-noised lung sounds by...

Research and analysis of cadmium residue in tomato leaves based on WT-LSSVR and Vis-NIR hyperspectral imaging.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The reliability and validity of Vis-NIR hyperspectral imaging were investigated for the determination of heavy metal content in tomato leaves under different cadmium stress. Besides, a method involving wavelet transform and least square support vecto...

Geometrical features for premature ventricular contraction recognition with analytic hierarchy process based machine learning algorithms selection.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Premature ventricular contraction is associated to the risk of coronary heart disease, and its diagnosis depends on a long time heart monitoring. For this purpose, monitoring through Holter devices is often used and computat...

Learning Spatial-Spectral-Temporal EEG Features With Recurrent 3D Convolutional Neural Networks for Cross-Task Mental Workload Assessment.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mental workload assessment is essential for maintaining human health and preventing accidents. Most research on this issue is limited to a single task. However, cross-task assessment is indispensable for extending a pre-trained model to new workload ...

MRI Brain Tumour Segmentation Using Hybrid Clustering and Classification by Back Propagation Algorithm.

Asian Pacific journal of cancer prevention : APJCP
Generally the segmentation refers, the partitioning of an image into smaller regions to identify or locate the region of abnormality. Even though image segmentation is the challenging task in medical applications, due to contrary image, local observa...

High quality imaging from sparsely sampled computed tomography data with deep learning and wavelet transform in various domains.

Medical physics
PURPOSE: Sparsely sampled computed tomography (CT) has been attracting attention as a technique that can reduce the high radiation dose of conventional CT. In general, iterative reconstruction techniques have been applied to sparsely sampled CT to re...