AIMC Topic: Wavelet Analysis

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Multi-scale aggregation network for colonoscopic polyp segmentation via frequency domain decoupling.

Scientific reports
Automated segmentation of colorectal polyps is of great significance for early screening and clinical intervention of colorectal cancer. However, the diversity of polyp morphology and the uneven contrast caused by illumination changes in colonoscopy ...

A fault diagnosis method for rotating machinery components based on enhanced YOLO v8 and integrated attention mechanism.

PloS one
Accurate fault diagnosis of rotating machinery components is the key to ensuring the safe operation of the mechanical system. Aiming at problems such as inaccurate detection of small target fault features and loss of fault information in the process ...

Earlier prediction of Parkinson's disease using cross non-decimated wavelet transform and machine learning algorithm.

Scientific reports
Parkinson's disease (PD) is a brain disorder, that affects a person's body movement causing stiffness, shaking and imbalance. Earlier detection of PD is a challenging task for researchers. In this paper, earlier detection of PD is performed using the...

Multiview state-of-health estimation for lithium-ion batteries using time-frequency image fusion and attention-based deep learning.

PloS one
Lithium-ion batteries are high-performance energy storage devices that have been widely used in a variety of applications. Accurate early-stage prediction of their remaining useful life is essential for preventing failures and mitigating safety risks...

Decoding covert visual attention of electroencephalography signals using continuous wavelet transform and deep learning approach.

Scientific reports
Covert visual attention decoding from EEG signals is a key challenge in cognitive neuroscience and brain-computer interface applications. Traditional approaches often rely on manual feature extraction and handcrafted pipelines, which limit scalabilit...

Detection of cognitive load using EEG signal and lifting wavelet transform with specific lead selection.

Biomedical physics & engineering express
Solving an arithmetic task is a complex assignment that includes sequencing, memory, fact retrieval, and decision making. Observation of the human brain's response to such activities is quite essential as it helps in the diagnosis of various diseases...

ECG beat classification with fractional order differentiator and machine learning techniques.

Biomedical physics & engineering express
Electrocardiogram (ECG) is essential for assessing heart function, but manual analysis is time-consuming and error-prone. Automated ECG analysis can improve early detection of cardiovascular diseases by accurately identifying abnormal beats despite s...

A Multimodal Convolutional Neural Network Model for Parkinson's Disease Diagnosis Based on Fused Handwriting Dynamics Signals.

Journal of medical systems
Parkinson's disease (PD) is a prevalent and complex neurodegenerative disorder, with early diagnosis playing a critical role in timely treatment and management. Handwriting dynamics has emerged as a promising biomarker for early detection of PD, yet ...

Epileptic seizure detection from electroencephalogram signals based on 1D CNN-LSTM deep learning model using discrete wavelet transform.

Scientific reports
Excessive electrical activity in the brain causes epileptic seizures which can be detected through Electroencephalogram (EEG) signals. The research aims to identify epileptic seizures using EEG records automatically. Firstly, EEG bands are extracted ...

Multimodal data driven deep learning based seismic impedance inversion optimization.

PloS one
Seismic impedance inversion is a geophysical technique that transforms seismic data into quantitative subsurface properties, primarily acoustic impedance. This process enables the identification of rock boundaries, hydrocarbon reservoirs, and litholo...