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Found 11 papers, 2 papers with code
Quantum-Based Combinatorial Optimization for Optimal Sensor Placement in Civil Structures
In this context, Structural Health Monitoring (SHM) arises as an especially interesting field to integrate and develop these new sensing capabilities, given the criticality of structural application for human life and the elevated costs of manual monitoring.
Towards an efficient Iris Recognition System on Embedded Devices
Iris Recognition (IR) is one of the market's most reliable and accurate biometric systems.
Learning to Predict Fitness for Duty using Near Infrared Periocular Iris Images
This research proposes a new database and method to detect the reduction of alertness conditions due to alcohol, drug consumption and sleepiness deprivation from Near-Infra-Red (NIR) periocular eye images.
Alcohol Consumption Detection from Periocular NIR Images Using Capsule Network
This research proposes a method to detect alcohol consumption from Near-Infra-Red (NIR) periocular eye images.
A Novel Capsule Neural Network Based Model for Drowsiness Detection Using Electroencephalography Signals
Due to the transient mental state of a human subject between alertness and drowsiness, automated drowsiness detection is a complex problem to tackle.
A generic physics-informed neural network-based framework for reliability assessment of multi-state systems
The gradient projection operation significantly mitigates the detrimental effects caused by the gradient interference when training PINN, thus accelerating the convergence speed of PINN to high-precision solutions to MSS reliability assessment.
An Uncertainty-Informed Framework for Trustworthy Fault Diagnosis in Safety-Critical Applications
There has been a growing interest in deep learning-based prognostic and health management (PHM) for building end-to-end maintenance decision support systems, especially due to the rapid development of autonomous systems.
Big Machinery Data Preprocessing Methodology for Data-Driven Models in Prognostics and Health Management
Sensor monitoring networks and advances in big data analytics have guided the reliability engineering landscape to a new era of big machinery data.
Physics-Informed Deep Learning: A Promising Technique for System Reliability Assessment
Considerable research has been devoted to deep learning-based predictive models for system prognostics and health management in the reliability and safety community.
Semantic Segmentation of Periocular Near-Infra-Red Eye Images Under Alcohol Effects
The purpose of the system is to measure the fitness for duty.
Uncovering the Underlying Physics of Degrading System Behavior Through a Deep Neural Network Framework: The Case of Remaining Useful Life Prognosis
Models are trained as a supervised regression and designed to output the RUL as well as a latent variable map that can be used and interpreted as the system's health indicator.
