11 citations · 21 across the 6 of their papers we have counts for
8 papers
Mamba-based Selective State Space Modeling Improves the Accuracy-Complexity Tradeoff of SmolVLA Vision-Language-Action Experts
Farida Mohsen, Thowayba Elkaffash, Mohammad Reza Chalak Qazani +3
Vision-language-action (VLA) models face a crucial tradeoff between their task success rate and the policy-call frequency. Executing a single action per inference () enables a…
A comparative and critical study of EEGNet for fNIRS-driven cognitive load classification
Mehshan Ahmed Khan, Houshyar Asadi, Li Zhang +8
Accurately classifying cognitive load from functional near-infrared spectroscopy (fNIRS) signals remains a significant challenge due to temporal variability, inter-subject differen…
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…
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…
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…
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…