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Now showing items 11-20 of 52
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 ...
Exploiting heterogeneity in operational neural networks by synaptic plasticity
(
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 ...
A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications
(
Academic Press
, 2021 , Article Review)
Monitoring structural damage is extremely important for sustaining and preserving the service life of civil structures. While successful monitoring provides resolute and staunch information on the health, serviceability, ...
Early Detection of Myocardial Infarction in Low-Quality Echocardiography
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Myocardial infarction (MI), or commonly known as heart attack, is a life-threatening health problem worldwide from which 32.4 million people suffer each year. Early diagnosis and treatment of MI are crucial to prevent ...
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 ...
Particle swarm clustering fitness evaluation with computational centroids
(
Elsevier B.V.
, 2017 , Article)
In this paper, we propose a new way to carry out fitness evaluation in dynamic Particle Swarm Clustering (PSC) with centroid-based encoding. Generally, the PSC fitness function is selected among the clustering validity ...
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 ...
Convolutional Sparse Support Estimator Network (CSEN): From Energy-Efficient Support Estimation to Learning-Aided Compressive Sensing
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Support estimation (SE) of a sparse signal refers to finding the location indices of the nonzero elements in a sparse representation. Most of the traditional approaches dealing with SE problems are iterative algorithms ...
Left Ventricular Wall Motion Estimation by Active Polynomials for Acute Myocardial Infarction Detection
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Echocardiogram (echo) is the earliest and the primary tool for identifying regional wall motion abnormalities (RWMA) in order to diagnose myocardial infarction (MI) or commonly known as heart attack. This paper proposes a ...
A Social Distance Estimation and Crowd Monitoring System for Surveillance Cameras
(
MDPI
, 2022 , Article)
Social distancing is crucial to restrain the spread of diseases such as COVID-19, but complete adherence to safety guidelines is not guaranteed. Monitoring social distancing through mass surveillance is paramount to develop ...