8 citations · 9 across the 3 of their papers we have counts for
6 papers
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…
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…
General Hazard Detection
Stephanie Ng, CP Lim, SueJen Looi +5
Hazard, as an abstract concept, is typically defined through cognitive-level logical reasoning rather than concrete examples. In contrast, existing hazard detection systems rely on…
Object-level Cross-view Geo-localization with Location Enhancement and Multi-Head Cross Attention
Zheyang Huang, Jagannath Aryal, Saeid Nahavandi +4
Cross-view geo-localization determines the location of a query image, captured by a drone or ground-based camera, by matching it to a geo-referenced satellite image. While traditio…
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…
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…