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Now showing items 11-20 of 40
Examining engineering students' perceptions of learner agency enactment in problem- and project-based learning using Q methodology
(
John Wiley and Sons Inc
, 2022 , Article)
Background: Few studies have reported how students enact learner agency in a team setting or examined what elements of team settings students perceive as more supportive of their learning in problem- and project-based ...
Augmented Reality Interface for Complex Anatomy Learning in the Central Nervous System: A Systematic Review
(
Hindawi
, 2020 , Article)
The medical system is facing the transformations with augmentation in the use of medical information systems, electronic records, smart, wearable devices, and handheld. The central nervous system function is to control the ...
An automated robust segmentation method for intravascular ultrasound images
(
World Scientific Publishing Co.
, 2014 , Book chapter)
It is widely known that the state of a patient's coronary heart disease can be better assessed using intravascular ultrasound (IVUS) than with more conventional angiography. Recent work has shown that segmentation and 3D ...
Advance Warning Methodologies for COVID-19 Using Chest X-Ray Images
(
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
(
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
(
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
(
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 ...