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Fault detection and severity identification of ball bearings by online condition monitoring
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Institute of Electrical and Electronics Engineers Inc.
, 2019 , Article)
This paper presents a fast, accurate, and simple systematic approach for online condition monitoring and severity identification of ball bearings. This approach utilizes compact one-dimensional (1-D) convolutional neural ...
Feature synthesis for image classification and retrieval via one-against-all perceptrons
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Springer London
, 2018 , Article)
Most existing content-based image retrieval and classification systems rely on low-level features which are automatically extracted from images. However, often these features lack the discrimination power needed for accurate ...
Real-Time Fault Detection and Identification for MMC Using 1-D Convolutional Neural Networks
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Institute of Electrical and Electronics Engineers Inc.
, 2019 , Article)
Automated early detection and identification of switch faults are essential in high-voltage applications. Modular multilevel converter (MMC) is a new and promising topology for such applications. MMC is composed of many ...
Robust R-Peak Detection in Low-Quality Holter ECGs Using 1D Convolutional Neural Network
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IEEE Computer Society
, 2022 , Article)
Objective: Noise and low quality of ECG signals acquired from Holter or wearable devices deteriorate the accuracy and robustness of R-peak detection algorithms. This paper presents a generic and robust system for R-peak ...
Real-time throughput prediction for cognitive Wi-Fi networks
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Academic Press
, 2020 , Article)
Wi-Fi as a wireless networking technology has become a widely acceptable commonplace. Over the course of time, the applications landscape of Wi-Fi networks is growing tremendously. The proliferation of new services is ...
3D Quantum Cuts for automatic segmentation of porous media in tomography images
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Elsevier Ltd
, 2022 , Article)
Binary segmentation of volumetric images of porous media is a crucial step towards gaining a deeper understanding of the factors governing biogeochemical processes at minute scales. Contemporary work primarily revolves ...
Real-Time Patient-Specific ECG Classification by 1D Self-Operational Neural Networks
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IEEE Computer Society
, 2021 , Article)
Despite the proliferation of numerous deep learning methods proposed for generic ECG classification and arrhythmia detection, compact systems with the real-time ability and high accuracy for classifying patient-specific ...
Early Bearing Fault Diagnosis of Rotating Machinery by 1D Self-Organized Operational Neural Networks
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Preventive maintenance of modern electric rotating machinery (RM) is critical for ensuring reliable operation, preventing unpredicted breakdowns and avoiding costly repairs. Recently many studies investigated machine ...
Self-organized Operational Neural Networks with Generative Neurons
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Elsevier Ltd
, 2021 , Article)
Operational Neural Networks (ONNs) have recently been proposed to address the well-known limitations and drawbacks of conventional Convolutional Neural Networks (CNNs) such as network homogeneity with the sole linear neuron ...
Exploiting heterogeneity in operational neural networks by synaptic plasticity
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Springer Science and Business Media Deutschland GmbH
, 2021 , Article)
The recently proposed network model, Operational Neural Networks (ONNs), can generalize the conventional Convolutional Neural Networks (CNNs) that are homogenous only with a linear neuron model. As a heterogenous network ...