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Robust R-Peak Detection in Low-Quality Holter ECGs Using 1D Convolutional Neural Network
(
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 ...
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
(
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 ...
Real-time phonocardiogram anomaly detection by adaptive 1D Convolutional Neural Networks
(
Elsevier B.V.
, 2020 , Article)
The heart sound signals (Phonocardiogram ? PCG) enable the earliest monitoring to detect a potential cardiovascular pathology and have recently become a crucial tool as a diagnostic test in outpatient monitoring to assess ...
Operational neural networks
(
Springer
, 2020 , Article)
Feed-forward, fully connected artificial neural networks or the so-called multi-layer perceptrons are well-known universal approximators. However, their learning performance varies significantly depending on the function ...
1D convolutional neural networks and applications: A survey
(
Academic Press
, 2021 , Article)
During the last decade, Convolutional Neural Networks (CNNs) have become the de facto standard for various Computer Vision and Machine Learning operations. CNNs are feed-forward Artificial Neural Networks (ANNs) with ...
Multifrequency Polsar Image Classification Using Dual-Band 1D Convolutional Neural Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
In this work, we propose a novel classification approach based on dual-band one-dimensional Convolutional Neural Networks (1D-CNNs) for classification of multifrequency polarimetric SAR (PolSAR) data. The proposed approach ...
Real-Time Glaucoma Detection from Digital Fundus Images Using Self-ONNs
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Glaucoma leads to permanent vision disability by damaging the optical nerve that transmits visual images to the brain. The fact that glaucoma does not show any symptoms as it progresses and cannot be stopped at the later ...
Learned vs. hand-designed features for ECG beat classification: A comprehensive study
(
Springer Verlag
, 2017 , Conference Paper)
In this study, in order to find out the best ECG classification performance we realized comparative evaluations among the state-of-the-art classifiers such as Convolutional Neural Networks (CNNs), multi-layer perceptrons ...