Zobrazeno 1 - 10
of 1 389
pro vyhledávání: '"NAHAVANDI, SAEID"'
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, 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:
Nahavandi, Saeid, Alizadehsani, Roohallah, Nahavandi, Darius, Lim, Chee Peng, Kelly, Kevin, Bello, Fernando
Automated industries lead to high quality production, lower manufacturing cost and better utilization of human resources. Robotic manipulator arms have major role in the automation process. However, for complex manipulation tasks, hard coding efficie
Externí odkaz:
http://arxiv.org/abs/2309.12560
Cloud Computing (CC) is revolutionizing the way IT resources are delivered to users, allowing them to access and manage their systems with increased cost-effectiveness and simplified infrastructure. However, with the growth of CC comes a host of secu
Externí odkaz:
http://arxiv.org/abs/2309.04911
Robot manipulation is an important part of human-robot interaction technology. However, traditional pre-programmed methods can only accomplish simple and repetitive tasks. To enable effective communication between robots and humans, and to predict an
Externí odkaz:
http://arxiv.org/abs/2309.04687
In recent years, the development of robotics and artificial intelligence (AI) systems has been nothing short of remarkable. As these systems continue to evolve, they are being utilized in increasingly complex and unstructured environments, such as au
Externí odkaz:
http://arxiv.org/abs/2309.02473
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:
Hasan, Mehedi, Abdar, Moloud, Khosravi, Abbas, Aickelin, Uwe, Lio', Pietro, Hossain, Ibrahim, Rahman, Ashikur, Nahavandi, Saeid
Although neural networks (especially deep neural networks) have achieved \textit{better-than-human} performance in many fields, their real-world deployment is still questionable due to the lack of awareness about the limitation in their knowledge. To
Externí odkaz:
http://arxiv.org/abs/2304.04906
Autor:
Sadeghi, Zahra, Alizadehsani, Roohallah, Cifci, Mehmet Akif, Kausar, Samina, Rehman, Rizwan, Mahanta, Priyakshi, Bora, Pranjal Kumar, Almasri, Ammar, Alkhawaldeh, Rami S., Hussain, Sadiq, Alatas, Bilal, Shoeibi, Afshin, Moosaei, Hossein, Hladik, Milan, Nahavandi, Saeid, Pardalos, Panos M.
XAI refers to the techniques and methods for building AI applications which assist end users to interpret output and predictions of AI models. Black box AI applications in high-stakes decision-making situations, such as medical domain have increased
Externí odkaz:
http://arxiv.org/abs/2304.01543