AIMC Topic: Wavelet Analysis

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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...

DEW: A wavelet approach of rare sound event detection.

PloS one
This paper presents a novel sound event detection (SED) system for rare events occurring in an open environment. Wavelet multiresolution analysis (MRA) is used to decompose the input audio clip of 30 seconds into five levels. Wavelet denoising is the...

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...

Damage detection of road domain waveform guardrail structure based on machine learning multi-module fusion.

PloS one
The current highway waveform guardrail recognition technology has encountered problems with low segmentation accuracy and strong noise interference. Therefore, an improved U-net semantic segmentation model is proposed to improve the efficiency of roa...

Coupling speckle noise suppression with image classification for deep-learning-aided ultrasound diagnosis.

Physics in medicine and biology
. During deep-learning-aided (DL-aided) ultrasound (US) diagnosis, US image classification is a foundational task. Due to the existence of serious speckle noise in US images, the performance of DL models may be degraded. Pre-denoising US images befor...

Enhancing speaker identification through reverberation modeling and cancelable techniques using ANNs.

PloS one
This paper introduces a method aiming at enhancing the efficacy of speaker identification systems within challenging acoustic environments characterized by noise and reverberation. The methodology encompasses the utilization of diverse feature extrac...

A novel fault diagnosis method for second-order bandpass filter circuit based on TQWT-CNN.

PloS one
To accurately locate faulty components in analog circuits, an analog circuit fault diagnosis method based on Tunable Q-factor Wavelet Transform(TQWT) and Convolutional Neural Network (CNN) is proposed in this paper. Firstly, the Grey Wolf algorithm (...

An emotion recognition method based on EWT-3D-CNN-BiLSTM-GRU-AT model.

Computers in biology and medicine
This has become a significant study area in recent years because of its use in brain-machine interaction (BMI). The robustness problem of emotion classification is one of the most basic approaches for improving the quality of emotion recognition syst...

Restoration of metabolic functional metrics from label-free, two-photon human tissue images using multiscale deep-learning-based denoising algorithms.

Journal of biomedical optics
SIGNIFICANCE: Label-free, two-photon excited fluorescence (TPEF) imaging captures morphological and functional metabolic tissue changes and enables enhanced understanding of numerous diseases. However, noise and other artifacts present in these image...

Distinctive approach in brain tumor detection and feature extraction using biologically inspired DWT method and SVM.

Scientific reports
Brain tumors result from uncontrolled cell growth, potentially leading to fatal consequences if left untreated. While significant efforts have been made with some promising results, the segmentation and classification of brain tumors remain challengi...