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Wavelet Analysis

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Deep learning approach for skin melanoma and benign classification using empirical wavelet decomposition.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Melanoma is a malignant skin cancer that causes high mortality. Early detection of melanoma can save patients' lives. The features of the skin lesion images can be extracted using computer techniques to differentiate early between melanom...

iAFPs-Mv-BiTCN: Predicting antifungal peptides using self-attention transformer embedding and transform evolutionary based multi-view features with bidirectional temporal convolutional networks.

Artificial intelligence in medicine
Globally, fungal infections have become a major health concern in humans. Fungal diseases generally occur due to the invading fungus appearing on a specific portion of the body and becoming hard for the human immune system to resist. The recent emerg...

Transfer learning and self-distillation for automated detection of schizophrenia using single-channel EEG and scalogram images.

Physical and engineering sciences in medicine
Schizophrenia (SZ) has been acknowledged as a highly intricate mental disorder for a long time. In fact, individuals with SZ experience a blurred line between fantasy and reality, leading to a lack of awareness about their condition, which can pose s...

A single-joint multi-task motor imagery EEG signal recognition method based on Empirical Wavelet and Multi-Kernel Extreme Learning Machine.

Journal of neuroscience methods
BACKGROUND: In the pursuit of finer Brain-Computer Interface commands, research focus has shifted towards classifying EEG signals for multiple tasks. While single-joint multitasking motor imagery provides support, distinguishing between EEG signals f...

Hybrid WT-CNN-GRU-based model for the estimation of reservoir water quality variables considering spatio-temporal features.

Journal of environmental management
Water quality indicators (WQIs), such as chlorophyll-a (Chl-a) and dissolved oxygen (DO), are crucial for understanding and assessing the health of aquatic ecosystems. Precise prediction of these indicators is fundamental for the efficient administra...

Exploring the potential of pretrained CNNs and time-frequency methods for accurate epileptic EEG classification: a comparative study.

Biomedical physics & engineering express
Prompt diagnosis of epilepsy relies on accurate classification of automated electroencephalogram (EEG) signals. Several approaches have been developed to characterize epileptic EEG data; however, none of them have exploited time-frequency data to eva...

Analysis of medical images super-resolution via a wavelet pyramid recursive neural network constrained by wavelet energy entropy.

Neural networks : the official journal of the International Neural Network Society
Recently, multi-resolution pyramid-based techniques have emerged as the prevailing research approach for image super-resolution. However, these methods typically rely on a single mode of information transmission between levels. In our approach, a wav...

Continuous wavelet transform and integration of discrete wavelet transform with principal component analysis and fuzzy inference system for the simultaneous determination of ethinyl estradiol and drospirenone in combined oral contraceptives.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this study, the spectrophotometric method integrated with continuous wavelet transform (CWT) and coupled discrete wavelet transform (DWT) with fuzzy inference system (FIS) was developed for the simultaneous determination of ethinyl estradiol (EE) ...

An Energy-Efficient ECG Processor With Ultra-Low-Parameter Multistage Neural Network and Optimized Power-of-Two Quantization.

IEEE transactions on biomedical circuits and systems
This work presents an energy-efficient ECG processor designed for Cardiac Arrhythmia Classification. The processor integrates a pre-processing and neural network accelerator, achieved through algorithm-hardware co-design to optimize hardware resource...

Smart Seizure Detection System: Machine Learning Based Model in Healthcare IoT.

Current aging science
BACKGROUND: Epilepsy, the tendency to have recurrent seizures, can have various causes, including brain tumors, genetics, stroke, brain injury, infections, and developmental disorders. Epileptic seizures are usually transient events. They normally le...