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Wavelet Analysis

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A Novel Computer-Vision Approach Assisted by 2D-Wavelet Transform and Locality Sensitive Discriminant Analysis for Concrete Crack Detection.

Sensors (Basel, Switzerland)
This study proposes FastCrackNet, a computationally efficient crack-detection approach. Instead of a computationally costly convolutional neural network (CNN), this technique uses an effective, fully connected network, which is coupled with a 2D-wave...

Classification Framework of the Bearing Faults of an Induction Motor Using Wavelet Scattering Transform-Based Features.

Sensors (Basel, Switzerland)
In the machine learning and data science pipelines, feature extraction is considered the most crucial component according to researchers, where generating a discriminative feature matrix is the utmost challenging task to achieve high classification a...

Wavelet LSTM for Fault Forecasting in Electrical Power Grids.

Sensors (Basel, Switzerland)
An electric power distribution utility is responsible for providing energy to consumers in a continuous and stable way. Failures in the electrical power system reduce the reliability indexes of the grid, directly harming its performance. For this rea...

A Novel Image-Based Diagnosis Method Using Improved DCGAN for Rotating Machinery.

Sensors (Basel, Switzerland)
Rotating machinery plays an important role in industrial systems, and faults in the machinery may damage the system health. A novel image-based diagnosis method using improved deep convolutional generative adversarial networks (DCGAN) is proposed for...

Seizure Types Classification by Generating Input Images With in-Depth Features From Decomposed EEG Signals for Deep Learning Pipeline.

IEEE journal of biomedical and health informatics
Electroencephalogram (EEG) based seizure types classification has not been addressed well, compared to seizure detection, which is very important for the diagnosis and prognosis of epileptic patients. The minuscule changes reflected in EEG signals am...

Deep Learning for Chondrogenic Tumor Classification through Wavelet Transform of Raman Spectra.

Sensors (Basel, Switzerland)
The grading of cancer tissues is still one of the main challenges for pathologists. The development of enhanced analysis strategies hence becomes crucial to accurately identify and further deal with each individual case. Raman spectroscopy (RS) is a ...

Power Equipment Fault Diagnosis Method Based on Energy Spectrogram and Deep Learning.

Sensors (Basel, Switzerland)
With the development of industrial manufacturing intelligence, the role of rotating machinery in industrial production and life is more and more important. Aiming at the problems of the complex and changeable working environment of rolling bearings a...

Enhanced Convolutional Neural Network for In Situ AUV Thruster Health Monitoring Using Acoustic Signals.

Sensors (Basel, Switzerland)
As the demand for ocean exploration increases, studies are being actively conducted on autonomous underwater vehicles (AUVs) that can efficiently perform various missions. To successfully perform long-term, wide-ranging missions, it is necessary to a...

Deep Learning with LPC and Wavelet Algorithms for Driving Fault Diagnosis.

Sensors (Basel, Switzerland)
Vehicle fault detection and diagnosis (VFDD) along with predictive maintenance (PdM) are indispensable for early diagnosis in order to prevent severe accidents due to mechanical malfunction in urban environments. This paper proposes an early voicepri...

WCNN3D: Wavelet Convolutional Neural Network-Based 3D Object Detection for Autonomous Driving.

Sensors (Basel, Switzerland)
Three-dimensional object detection is crucial for autonomous driving to understand the driving environment. Since the pooling operation causes information loss in the standard CNN, we designed a wavelet-multiresolution-analysis-based 3D object detect...