Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Armin Salimi-Badr"'
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:
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:
Christian Darlot, Armin Salimi-Badr, Mitra Asadi-Eydivand, Zahra Ghorrati, Mohammad Mehdi Ebadzadeh
Publikováno v:
IEEE Access, Vol 8, Pp 110859-110879 (2020)
In this paper a comprehensive system-level computational model of oculomotor pathways is presented. This model shows the necessity of embedding internal models of muscles biomechanics in the cerebellar Vermis to realize fast saccadic eye movements ba
Externí odkaz:
https://doaj.org/article/ca3a6c7badc241c3a094dff86ab3866c
Autor:
Athena Abdi, Armin Salimi-Badr
Publikováno v:
IEEE Transactions on Sustainable Computing. :1-13
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7ac2e072113d7166d62f15d82d178f9f
https://doi.org/10.1109/tsusc.2023.3244081
https://doi.org/10.1109/tsusc.2023.3244081
Publikováno v:
Applied Intelligence. 53:15656-15682
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::646557d03a92de893ceed9fc8abca604
https://doi.org/10.1007/s10489-022-04276-8
https://doi.org/10.1007/s10489-022-04276-8
Publikováno v:
Neurocomputing. 470:139-153
In this paper, a novel learning approach to train fuzzy neural networks’ parameters based on calculating the desired outputs of their rules, is proposed. We describe the desired outputs of fuzzy rules as values that make the output error equal to t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d4f7e8b776370099add19fd354c7a51
https://doi.org/10.1016/j.neucom.2021.10.103
https://doi.org/10.1016/j.neucom.2021.10.103
Publikováno v:
2022 12th International Conference on Computer and Knowledge Engineering (ICCKE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f0808229c258aff72f0eb5b906c5965b
https://doi.org/10.1109/iccke57176.2022.9960115
https://doi.org/10.1109/iccke57176.2022.9960115
Publikováno v:
2022 27th International Computer Conference, Computer Society of Iran (CSICC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf715552034dec4e969d3b56c2a8340a
https://doi.org/10.1109/csicc55295.2022.9780500
https://doi.org/10.1109/csicc55295.2022.9780500
Publikováno v:
2021 11th International Conference on Computer Engineering and Knowledge (ICCKE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6dbd3e615bda65b1a3aa4f0bd9a99978
https://doi.org/10.1109/iccke54056.2021.9721465
https://doi.org/10.1109/iccke54056.2021.9721465
Autor:
Armin Salimi-Badr
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:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e4a02c500daabb190fd548ba38c1e45d
http://arxiv.org/abs/2108.08704
http://arxiv.org/abs/2108.08704
