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Islanding detection in DC ring microgrid using improved complete ensemble empirical mode decomposition with adaptive noise and multi-class AdaBoost algorithm
To meet the energy demand and increase the reliability, DC microgrids are mainly preferred in the present era. Particularly, photovoltaic-based DC...
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VMD-Based Ensembled SMOTEBoost for Imbalanced Multi-class Rotor Mass Imbalance Fault Detection and Diagnosis Under Industrial Noise
PurposeThe purpose of this study is to investigate rotor imbalance fault diagnosis for multi-class imbalanced noisy data in rotor-bearing systems....
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Investigating Machine Learning Techniques Used for the Detection of Class Noise in Data: A Systematic Literature Review
Data provides valuable information and insights and assists in making strategic decisions. The quality of the data is distorted by noise, which...
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Noise Resistant Cross-Entropy Loss for Robust Learning in Pin Defect Detection with Noisy Class Label
Pins, which is used to fix nut, is important for transmission line, accurately detect pin defects efficiently is of great interests recently....
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Novelty class detection in machine learning-based condition diagnosis
Industrial plant machines have a significantly lower frequency of defective data than the frequency of normal data. For this reason, machine learning...
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A real-valued label noise cleaning method based on ensemble iterative filtering with noise score
Real-world data always contain noise for a variety of reasons. In a regression task, noisy labels interfere with the construction of an accurate...
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Thermal noise-driven resonant sensors
MEMS/NEMS resonant sensors hold promise for minute mass and force sensing. However, one major challenge is that conventional externally driven...
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Class-biased sarcasm detection using BiLSTM variational autoencoder-based synthetic oversampling
Recent research works have established the importance of sarcasm detection in the domain of sentiment analysis. Automatic sarcasm detection using...
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Mathematical Modeling of Signal Detection in Non-gaussian Correlated Noise
The development of signal detection systems requires complete information about the type of random processes distributions in communication channels...
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Robust coherent and incoherent statistics for detection of hidden periodicity in models with non-Gaussian additive noise
We address the issue of detecting hidden periodicity when the signal exhibits periodic correlation, but is additionally affected by non-Gaussian...
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Comprehensive Approach for Image Noise Analysis: Detection, Classification, Estimation, and Denoising
Image noise is undesirable that can negatively affect the quality of digital images. It reduces the image quality and increases the processing...
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Welding fault detection and diagnosis using one-class SVM with distance substitution kernels and random convolutional kernel transform
Welding defect detection in the manufacturing of hot water tanks is still often performed by human visual inspection or with the help of classical...
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Weakly-supervised structural surface crack detection algorithm based on class activation map and superpixel segmentation
This paper proposes a weakly-supervised structural surface crack detection algorithm that can detect the crack area in an image with low data...
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One-Class Convolutional Neural Network (OC-CNN) Model for Rapid Bridge Damage Detection Using Bridge Response Data
This study proposes a numerical investigation for rapid bridge damage detection based on a semi-supervised deep learning (DL) model and a damage...
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AI-enabled dental caries detection using transfer learning and gradient-based class activation map**
Dental caries detection holds the key to unlocking brighter smiles and healthier lives by identifying one of the most common oral health issues early...
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Noise-immune image blur detection via sequency spectrum truncation
Blur detection is aimed to differentiate the blurry and sharp regions from a given image. This task has attracted much attention in recent years due...
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Investigation of automatic spindle detection in sleep EEG signals contaminated with noise and artifact sources
Electroencephalography (EEG) serves as the gold standard for noninvasive diagnosis of different types of sleep disorders such as sleep apnea,...
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Detection of Signal Integrity Issues in Vibration Monitoring Using One-Class Support Vector Machine
This paper presents an analysis of the common signal integrity issues in vibration monitoring caused by sensor saturation and signal distortion, or...
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One-class machine learning approach for localized damage detection
With the advancement in computing power and sensing technology in the last decade, smart monitoring and decision-making approaches are becoming more...
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Assessing the Acoustic Noise in Intensive Care Units via Deep Learning Technique
Intensive care unit (ICU) noise is a critical and often overlooked issue, impacting patient recovery and healthcare staff well-being. Existing...
