Zobrazeno 1 - 10
of 97
pro vyhledávání: '"Salimi-Badr A"'
Autor:
Rashnu, Alireza, Salimi-Badr, Armin
Efficient early diagnosis is paramount in addressing the complexities of Parkinson's disease because timely intervention can substantially mitigate symptom progression and improve patient outcomes. In this paper, we present a pioneering deep learning
Externí odkaz:
http://arxiv.org/abs/2404.15335
Publikováno v:
IEEE Access, 2024
In this study, we leverage a deep learning-based method for the automatic diagnosis of schizophrenia using EEG brain recordings. This approach utilizes generative data augmentation, a powerful technique that enhances the accuracy of the diagnosis. To
Externí odkaz:
http://arxiv.org/abs/2310.16867
Publikováno v:
IEEE Open Journal of Vehicular Technology, Vol 6, Pp 34-51 (2025)
Autonomous navigation is a formidable challenge for autonomous aerial vehicles operating in dense or dynamic environments. This paper proposes a path-planning approach based on deep reinforcement learning for a quadrotor equipped with only a monocula
Externí odkaz:
https://doaj.org/article/994f66629a7444d5ac353e0824dea03f
Autor:
Salimi-Badr, Armin
Publikováno v:
Neurocomputing, vol. 579, pp 127437, 2024
An important constraint of Fuzzy Inference Systems (FIS) is their structured rules defined based on evaluating all input variables. Indeed, the length of all fuzzy rules and the number of input variables are equal. However, in many decision-making pr
Externí odkaz:
http://arxiv.org/abs/2211.00599
Publikováno v:
In Applied Soft Computing January 2025 169
Autor:
Mehrshad Saadatinia, Armin Salimi-Badr
Publikováno v:
IEEE Access, Vol 12, Pp 98379-98392 (2024)
Schizophrenia is an example of a rare mental disorder that is challenging to diagnose using conventional methods. Deep learning methods have been extensively employed to aid in the diagnosis of schizophrenia. However, their efficacy relies heavily on
Externí odkaz:
https://doaj.org/article/51a6b1910c474e88a13303f6d84bb327
Autor:
Abdi, Athena, Salimi-Badr, Armin
In this paper, an online task scheduling and mapping method based on a fuzzy neural network (FNN) learned by an evolutionary multi-objective algorithm (NSGA-II) to jointly optimize the main design challenges of heterogeneous MPSoCs is proposed. In th
Externí odkaz:
http://arxiv.org/abs/2203.14717
Autor:
Abdi, Athena, Salimi-badr, Armin
Publikováno v:
In Sustainable Computing: Informatics and Systems September 2024 43
Publikováno v:
Applied Intelligence, 2022
In this paper, an interpretable classifier using an interval type-2 fuzzy neural network for detecting patients suffering from Parkinson's Disease (PD) based on analyzing the gait cycle is presented. The proposed method utilizes clinical features ext
Externí odkaz:
http://arxiv.org/abs/2109.02442
Autor:
Salimi-Badr, Armin
Publikováno v:
Applied Soft Computing, vol. 115, pp. 108258, 2022
In this paper, a new interval type-2 fuzzy neural network able to construct non-separable fuzzy rules with adaptive shapes is introduced. To reflect the uncertainty, the shape of fuzzy sets considered to be uncertain. Therefore, a new form of interva
Externí odkaz:
http://arxiv.org/abs/2108.08704