AIMC Topic: Noise

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An Improved Bearing Fault Diagnosis Model of Variational Mode Decomposition Based on Linked Extension Neural Network.

Computational intelligence and neuroscience Apr 25, 2022
In bearing fault diagnosis, due to the insufficient obtained supervised data and the inevitable noise contained in the vibration signals, the problem of clustering bearing fault diagnosis with imbalanced data containing noise is caused. Thanks to the...
Cluster Analysis Algorithms Vibration Noise Neural Networks, Computer
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Two-Stage CNN Model for Joint Demosaicing and Denoising of Burst Bayer Images.

Computational intelligence and neuroscience Apr 4, 2022
In the classical image processing pipeline, demosaicing and denoising are separated steps that may interfere with each other. Joint demosaicing and denoising utilizes the shared image prior information to guide the image recovery process. It is expec...
Image Processing, Computer-Assisted Noise Neural Networks, Computer Normal Distribution Signal-To-Noise Ratio
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Multi-Stream Convolutional Neural Networks for Rotating Machinery Fault Diagnosis under Noise and Trend Items.

Sensors (Basel, Switzerland) Apr 1, 2022
In recent years, rotating machinery fault diagnosis methods based on convolutional neural network have achieved much success. However, in real industrial environments, interfering signals are unavoidable, which may reduce the accuracy of fault diagno...
Neural Networks, Computer Physical Therapy Modalities Vibration Noise Algorithms
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Noise Immunity and Robustness Study of Image Recognition Using a Convolutional Neural Network.

Sensors (Basel, Switzerland) Feb 6, 2022
The problem surrounding convolutional neural network robustness and noise immunity is currently of great interest. In this paper, we propose a technique that involves robustness estimation and stability improvement. We also examined the noise immunit...
Recognition, Psychology Uncertainty Image Processing, Computer-Assisted Probability Neural Networks, Computer Noise
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Deep Learning Approaches for Robust Time of Arrival Estimation in Acoustic Emission Monitoring.

Sensors (Basel, Switzerland) Jan 31, 2022
In this work, different types of artificial neural networks are investigated for the estimation of the time of arrival (ToA) in acoustic emission (AE) signals. In particular, convolutional neural network (CNN) models and a novel capsule neural networ...
Neural Networks, Computer Deep Learning Acoustics Noise Data Collection
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Sound Event Detection by Pseudo-Labeling in Weakly Labeled Dataset.

Sensors (Basel, Switzerland) Dec 15, 2021
Weakly labeled sound event detection (WSED) is an important task as it can facilitate the data collection efforts before constructing a strongly labeled sound event dataset. Recent high performance in deep learning-based WSED's exploited using a segm...
Sound Noise Hearing Neural Networks, Computer Acoustics
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Deep neural network models reveal interplay of peripheral coding and stimulus statistics in pitch perception.

Nature communications Dec 14, 2021
Perception is thought to be shaped by the environments for which organisms are optimized. These influences are difficult to test in biological organisms but may be revealed by machine perceptual systems optimized under different conditions. We invest...
Pitch Perception Noise Sound Neural Networks, Computer Music Humans Pitch Discrimination Cochlea Acoustic Stimulation
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Noise Eliminated Ensemble Empirical Mode Decomposition Scalogram Analysis for Rotating Machinery Fault Diagnosis.

Sensors (Basel, Switzerland) Dec 4, 2021
Rotating machinery is one of the major components of industries that suffer from various faults due to the constant workload. Therefore, a fast and reliable fault diagnosis method is essential for machine condition monitoring. In this study, noise el...
Wavelet Analysis Intelligence Vibration Neural Networks, Computer Noise
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GroningenNet: Deep Learning for Low-Magnitude Earthquake Detection on a Multi-Level Sensor Network.

Sensors (Basel, Switzerland) Dec 2, 2021
Automatic detection of low-magnitude earthquakes has become an increasingly important research topic in recent years due to a sharp increase in induced seismicity around the globe. The detection of low-magnitude seismic events is essential for micros...
Neural Networks, Computer Earthquakes Deep Learning Noise Algorithms
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A Hybrid Approach for Noise Reduction in Acoustic Signal of Machining Process Using Neural Networks and ARMA Model.

Sensors (Basel, Switzerland) Dec 1, 2021
Intelligent machining has become an important part of manufacturing systems because of the increased demand for productivity. Tool condition monitoring is an integral part of these systems. Airborne acoustic emission from the machining process is a v...
Signal-To-Noise Ratio Acoustics Neural Networks, Computer Noise Algorithms
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