AIMC Topic: Wavelet Analysis

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Transfer Learning in ECG Classification from Human to Horse Using a Novel Parallel Neural Network Architecture.

Scientific reports
Automatic or semi-automatic analysis of the equine electrocardiogram (eECG) is currently not possible because human or small animal ECG analysis software is unreliable due to a different ECG morphology in horses resulting from a different cardiac inn...

SVM-Enabled Intelligent Genetic Algorithmic Model for Realizing Efficient Universal Feature Selection in Breast Cyst Image Acquired via Ultrasound Sensing Systems.

Sensors (Basel, Switzerland)
In recent years, there are several cost-effective intelligent sensing systems such as ultrasound imaging systems for visualizing the internal body structures of the body. Further, such intelligent sensing systems such as ultrasound systems have been ...

Forecasting stock prices with long-short term memory neural network based on attention mechanism.

PloS one
The stock market is known for its extreme complexity and volatility, and people are always looking for an accurate and effective way to guide stock trading. Long short-term memory (LSTM) neural networks are developed by recurrent neural networks (RNN...

A novel multi-modal machine learning based approach for automatic classification of EEG recordings in dementia.

Neural networks : the official journal of the International Neural Network Society
Electroencephalographic (EEG) recordings generate an electrical map of the human brain that are useful for clinical inspection of patients and in biomedical smart Internet-of-Things (IoT) and Brain-Computer Interface (BCI) applications. From a signal...

A Tunable-Q wavelet transform and quadruple symmetric pattern based EEG signal classification method.

Medical hypotheses
Electroencephalography (EEG) signals have been widely used to diagnose brain diseases for instance epilepsy, Parkinson's Disease (PD), Multiple Skleroz (MS), and many machine learning methods have been proposed to develop automated disease diagnosis ...

Utilizing wavelet deep learning network to classify different states of task-fMRI for verifying activation regions.

The International journal of neuroscience
We propose a convolutional neural network (CNN) based on wavelet for verifying the activation regions decided with statistical analysis. Because the functional magnetic resonance imaging (fMRI) data contains lots of noises, it is difficult to get th...

Improved detection of Parkinsonian resting tremor with feature engineering and Kalman filtering.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Accurate and reliable detection of tremor onset in Parkinson's disease (PD) is critical to the success of adaptive deep brain stimulation (aDBS) therapy. Here, we investigated the potential use of feature engineering and machine learning m...

Two stage residual CNN for texture denoising and structure enhancement on low dose CT image.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: X-ray computed tomography (CT) plays an important role in modern medical science. Human health problems caused by CT radiation have attracted the attention of the academic community widely. Reducing radiation dose results in...

EEG-based single-channel authentication systems with optimum electrode placement for different mental activities.

Biomedical journal
BACKGROUND: Electroencephalogram (EEG) signals of a brain contain a unique pattern for each person and the potential for biometric applications. Authentication and security is a very important issue in our life and brainwave-based authentication is a...