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Content-based image retrieval with compact deep convolutional features
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Elsevier B.V.
, 2017 , Article)
Convolutional neural networks (CNNs) with deep learning have recently achieved a remarkable success with a superior performance in computer vision applications. Most of CNN-based methods extract image features at the last ...
A Generic Intelligent Bearing Fault Diagnosis System Using Compact Adaptive 1D CNN Classifier
(
Springer New York LLC
, 2019 , Article)
Timely and accurate bearing fault detection and diagnosis is important for reliable and safe operation of industrial systems. In this study, performance of a generic real-time induction bearing fault diagnosis system ...
Wireless and real-time structural damage detection: A novel decentralized method for wireless sensor networks
(
Elsevier
, 2018 , Article)
© 2018 Elsevier Ltd Being an alternative to conventional wired sensors, wireless sensor networks (WSNs) are extensively used in Structural Health Monitoring (SHM) applications. Most of the Structural Damage Detection (SDD) ...
Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks
(
Academic Press
, 2017 , Article)
Structural health monitoring (SHM) and vibration-based structural damage detection have been a continuous interest for civil, mechanical and aerospace engineers over the decades. Early and meticulous damage detection has ...
Novel Actuator Fault Diagnosis Framework for Multizone HVAC Systems Using 2-D Convolutional Neural Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Heating, ventilation, and air conditioning (HVAC) systems are used to condition the indoor environment in buildings. They can be subjected to malfunctioning since they are the most extensively operated buildings' components ...
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 ...
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 ...
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 ...
An intelligent and low-cost eye-tracking system for motorized wheelchair control
(
MDPI AG
, 2020 , Article)
In the 34 developed and 156 developing countries, there are ~132 million disabled people who need a wheelchair, constituting 1.86% of the world population. Moreover, there are millions of people suffering from diseases ...