12 citations · 40 across the 9 of their papers we have counts for
9 papers
Learning-Based Approximate Nonlinear Model Predictive Control Motion Cueing
Camilo Gonzalez Arango, Houshyar Asadi, Mohammad Reza Chalak Qazani +1
Motion Cueing Algorithms (MCAs) encode the movement of simulated vehicles into movement that can be reproduced with a motion simulator to provide a realistic driving experience wit…
A nonlinear real time capable motion cueing algorithm based on deep reinforcement learning
Hendrik Scheidel, Camilo Gonzalez, Houshyar Asadi +4
In motion simulation, motion cueing algorithms are used for the trajectory planning of the motion simulator platform, where workspace limitations prevent direct reproduction of ref…
Predicting cognitive load in immersive driving scenarios with a hybrid CNN-RNN model
Mehshan Ahmed Khan, Houshyar Asadi, Mohammad Reza Chalak Qazani +3
One debatable issue in traffic safety research is that cognitive load from sec-ondary tasks reduces primary task performance, such as driving. Although physiological signals have b…
Functional near-infrared spectroscopy (fNIRS) and Eye tracking for Cognitive Load classification in a Driving Simulator Using Deep Learning
Mehshan Ahmed Khan, Houshyar Asadi, Mohammad Reza Chalak Qazani +2
Motion simulators allow researchers to safely investigate the interaction of drivers with a vehicle. However, many studies that use driving simulator data to predict cognitive load…
Enhancing Cognitive Workload Classification Using Integrated LSTM Layers and CNNs for fNIRS Data Analysis
Mehshan Ahmed Khan, Houshyar Asadi, Mohammad Reza Chalak Qazani +6
Functional near-infrared spectroscopy (fNIRS) is employed as a non-invasive method to monitor functional brain activation by capturing changes in the concentrations of oxygenated h…
Neural Networks for Fast Optimisation in Model Predictive Control: A Review
Camilo Gonzalez, Houshyar Asadi, Lars Kooijman +1
Model Predictive Control (MPC) is an optimal control algorithm with strong stability and robustness guarantees. Despite its popularity in robotics and industrial applications, the…
Uncertainty Aware Neural Network from Similarity and Sensitivity
H M Dipu Kabir, Subrota Kumar Mondal, Sadia Khanam +8
Researchers have proposed several approaches for neural network (NN) based uncertainty quantification (UQ). However, most of the approaches are developed considering strong assumpt…
A Deep Reinforcement Learning Based Motion Cueing Algorithm for Vehicle Driving Simulation
Hendrik Scheidel, Houshyar Asadi, Tobias Bellmann +3
Motion cueing algorithms (MCA) are used to control the movement of motion simulation platforms (MSP) to reproduce the motion perception of a real vehicle driver as accurately as po…
CoV-TI-Net: Transferred Initialization with Modified End Layer for COVID-19 Diagnosis
Sadia Khanam, Mohammad Reza Chalak Qazani, Subrota Kumar Mondal +8
This paper proposes transferred initialization with modified fully connected layers for COVID-19 diagnosis. Convolutional neural networks (CNN) achieved a remarkable result in imag…