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السجلات المعروضة 11 -- 20 من 36
Advance Warning Methodologies for COVID-19 Using Chest X-Ray Images
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Coronavirus disease 2019 (COVID-19) has rapidly become a global health concern after its first known detection in December 2019. As a result, accurate and reliable advance warning system for the early diagnosis of COVID-19 ...
Automatic signal abnormality detection using time-frequency features and machine learning: A newborn EEG seizure case study
(
Elsevier B.V.
, 2016 , Article)
Time-frequency (TF) based machine learning methodologies can improve the design of classification systems for non-stationary signals. Using selected TF distributions (TFDs), TF feature extraction is performed on multi-channel ...
Efficiency validation of one dimensional convolutional neural networks for structural damage detection using a SHM benchmark data
(
International Institute of Acoustics and Vibration, IIAV
, 2018 , Conference Paper)
In this paper, a novel one dimensional convolution neural network (1D-CNN) based structural damage assessment technique is validated with a benchmark study published by IASC-ASCE Structural Health Monitoring Task Group in ...
A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications
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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, ...
Heterogeneous Multilayer Generalized Operational Perceptron
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
The traditional multilayer perceptron (MLP) using a McCulloch-Pitts neuron model is inherently limited to a set of neuronal activities, i.e., linear weighted sum followed by nonlinear thresholding step. Previously, generalized ...
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 ...
Face-Fake-Net: The Deep Learning Method for Image Face Anti-Spoofing Detection : 45
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
Due to the increasingly growing demand for user identification on cell phones, PCs, laptops, and so on, face anti-spoofing has risen to significance and is an active research area in academia and industry. The detection ...
Multimodal deep learning approach for Joint EEG-EMG Data compression and classification
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Institute of Electrical and Electronics Engineers Inc.
, 2017 , Conference Paper)
In this paper, we present a joint compression and classification approach of EEG and EMG signals using a deep learning approach. Specifically, we build our system based on the deep autoencoder architecture which is designed ...
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. IoT is one of the fastest developing fields in the history of computing, with an ...
EEG-based Analysis Study for Patients Receiving Intravenous Antibiotic Medication
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
In this paper, we conduct a biological data collection and analysis study for patients undergoing routine planned intravenous antibiotic treatment. The acquired data (i.e., Electroencephalogram (EEG), temperature and blood ...