Zobrazeno 1 - 10
of 167
pro vyhledávání: '"Asadi, Houshyar"'
Autor:
Khan, Mehshan Ahmed, Asadi, Houshyar, Qazani, Mohammad Reza Chalak, Arogbonlo, Adetokunbo, Nahavandi, Saeid, Lim, Chee Peng
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 been extensively used in driving-related research to assess cognitive l
Externí odkaz:
http://arxiv.org/abs/2408.06350
Autor:
Khan, Mehshan Ahmed, Asadi, Houshyar, Qazani, Mohammad Reza Chalak, Lim, Chee Peng, Nahavandi, Saied
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 only employ two levels of workload, leaving a gap in research on empl
Externí odkaz:
http://arxiv.org/abs/2408.06349
Autor:
Khan, Mehshan Ahmed, Asadi, Houshyar, Qazani, Mohammad Reza Chalak, Arogbonlo, Adetokunbo, Pedrammehr, Siamak, Anwar, Adnan, Bhatti, Asim, Nahavandi, Saeid, Lim, Chee Peng
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 haemoglobin (HbO) and deoxygenated haemo-globin (HbR). Various machine
Externí odkaz:
http://arxiv.org/abs/2407.15901
Autor:
Jafarizadeh, Ali, Maleki, Shadi Farabi, Pouya, Parnia, Sobhi, Navid, Abdollahi, Mirsaeed, Pedrammehr, Siamak, Lim, Chee Peng, Asadi, Houshyar, Alizadehsani, Roohallah, Tan, Ru-San, Islam, Sheikh Mohammad Shariful, Acharya, U. Rajendra
Retinopathy of prematurity (ROP) is a severe condition affecting premature infants, leading to abnormal retinal blood vessel growth, retinal detachment, and potential blindness. While semi-automated systems have been used in the past to diagnose ROP-
Externí odkaz:
http://arxiv.org/abs/2402.09975
Autor:
Abdollahi, Mirsaeed, Jafarizadeh, Ali, Asbagh, Amirhosein Ghafouri, Sobhi, Navid, Pourmoghtader, Keysan, Pedrammehr, Siamak, Asadi, Houshyar, Alizadehsani, Roohallah, Tan, Ru-San, Acharya, U. Rajendra
Background: Cardiovascular diseases (CVDs) are the leading cause of death globally. The use of artificial intelligence (AI) methods - in particular, deep learning (DL) - has been on the rise lately for the analysis of different CVD-related topics. Th
Externí odkaz:
http://arxiv.org/abs/2311.07609
Model Predictive Control (MPC) is an optimal control algorithm with strong stability and robustness guarantees. Despite its popularity in robotics and industrial applications, the main challenge in deploying MPC is its high computation cost, stemming
Externí odkaz:
http://arxiv.org/abs/2309.02668
Autor:
Kabir, H M Dipu, Mondal, Subrota Kumar, Khanam, Sadia, Khosravi, Abbas, Rahman, Shafin, Qazani, Mohammad Reza Chalak, Alizadehsani, Roohallah, Asadi, Houshyar, Mohamed, Shady, Nahavandi, Saeid, Acharya, U Rajendra
Publikováno v:
Applied Soft Computing, 2023
Researchers have proposed several approaches for neural network (NN) based uncertainty quantification (UQ). However, most of the approaches are developed considering strong assumptions. Uncertainty quantification algorithms often perform poorly in an
Externí odkaz:
http://arxiv.org/abs/2304.14925
Autor:
Scheidel, Hendrik, Asadi, Houshyar, Bellmann, Tobias, Seefried, Andreas, Mohamed, Shady, Nahavandi, Saeid
In the field of motion simulation, the level of immersion strongly depends on the motion cueing algorithm (MCA), as it transfers the reference motion of the simulated vehicle to a motion of the motion simulation platform (MSP). The challenge for the
Externí odkaz:
http://arxiv.org/abs/2304.07600
Autor:
Khanam, Sadia, Qazani, Mohammad Reza Chalak, Mondal, Subrota Kumar, Kabir, H M Dipu, Sabyasachi, Abadhan S., Asadi, Houshyar, Kumar, Keshav, Tabarsinezhad, Farzin, Mohamed, Shady, Khorsavi, Abbas, Nahavandi, Saeid
This paper proposes transferred initialization with modified fully connected layers for COVID-19 diagnosis. Convolutional neural networks (CNN) achieved a remarkable result in image classification. However, training a high-performing model is a very
Externí odkaz:
http://arxiv.org/abs/2209.09556
Publikováno v:
In Fuel 15 September 2024 372
