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Real-Time Patient-Specific ECG Classification by 1D Self-Operational Neural Networks
(
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
(
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 ...
Progressive Operational Perceptrons
(
Elsevier B.V.
, 2017 , Article)
There are well-known limitations and drawbacks on the performance and robustness of the feed-forward, fully-connected Artificial Neural Networks (ANNs), or the so-called Multi-Layer Perceptrons (MLPs). In this study we ...
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 ...
Face segmentation in thumbnail images by data-adaptive convolutional segmentation networks
(
IEEE Computer Society
, 2016 , Conference Paper)
In this study we address the problem of face segmentation in thumbnail images. While there have been several approaches for face detection, none performs detection in such low resolution and segmentation with pixel accuracy. ...
Generalized Operational Classifiers for Material Identification
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Material is one of the intrinsic features of objects, and consequently material recognition plays an important role in image understanding. The same material may have various shapes and appearance, while keeping the same ...
Convolutional neural networks for real-time and wireless damage detection
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Springer New York LLC
, 2020 , Conference Paper)
Structural damage detection methods available for structural health monitoring applications are based on data preprocessing, feature extraction, and feature classification. The feature classification task requires considerable ...
Control of plate vibrations with artificial neural networks and piezoelectricity
(
Springer New York LLC
, 2020 , Conference Paper)
This paper presents a method for active vibration control of smart thin cantilever plates. For model formulation needed for controller design and simulations, finite difference technique is used on the cantilever plate ...
Structural health monitoring with self-organizing maps and artificial neural networks
(
Springer New York LLC
, 2020 , Conference Paper)
The use of self-organizing maps and artificial neural networks for structural health monitoring is presented in this paper. The authors recently developed a nonparametric structural damage detection algorithm for extracting ...