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Meisam Yadollahzadeh Tabari
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2020 – today
- 2024
- [j15]Rahman Keramati Hatkeposhti
, Meisam Yadollahzadeh Tabari
, Mehdi GolsorkhtabariAmiri
:
Providing an Approach for Early Prediction of Fall in Human Activities Based on Wearable Sensor Data and the Use of Deep Learning Algorithms. Comput. J. 67(2): 658-673 (2024) - [j14]Amir Tehrani, Meisam Yadollahzadeh Tabari
, Aidin Zehtab-Salmasi, Rasul Enayatifar:
Wearable Sensor-Based Human Activity Recognition System Employing Bi-LSTM Algorithm. Comput. J. 67(3): 961-975 (2024) - [j13]Elias Ramzani, Meisam Yadollahzadeh Tabari
, Mehdi Golsorkhtabaramiri, Ali A. Pouyan
:
Diagnosing of Parkinson's disease based on hand drawing analysis using Bi-Directional LSTM equipped with fuzzy inferential soft-max classifier. Int. J. Imaging Syst. Technol. 34(1) (2024) - [j12]Motahare Ghavidel, Meisam Yadollahzadeh Tabari, Mehdi GolsorkhtabariAmiri:
Customer analysis using a deep inferarer classifier and a variable-sensitive clustering algorithm optimized by the Cuckoo search method. J. Intell. Fuzzy Syst. 46(1): 339-353 (2024) - 2022
- [j11]Masoumeh Bourjandi, Meisam Yadollahzadeh Tabari
, Mehdi Golsorkhtabaramiri:
Combined deep centralized coordinate learning and hybrid loss for human activity recognition. Concurr. Comput. Pract. Exp. 34(22) (2022) - [j10]Reza Shakerian, Meisam Yadollahzadeh Tabari
, Seyed Yaser Bozorgi Rad:
Proposing a Fuzzy Soft-max-based classifier in a hybrid deep learning architecture for human activity recognition. IET Biom. 11(2): 171-186 (2022) - [j9]Mahbubeh Nazarloo, Meisam Yadollahzadeh Tabari
, Homayun Motameni:
Online multi-object tracking based on time and frequency domain features. IET Comput. Digit. Tech. 16(1): 19-28 (2022) - [j8]Azam Qarehkhani, Mehdi Golsorkhtabaramiri
, Hosein Mohamadi, Meisam Yadollahzadeh Tabari
:
Solving the target coverage problem in multilevel wireless networks capable of adjusting the sensing angle using continuous learning automata. IET Commun. 16(2): 151-163 (2022) - [j7]Masoumeh Bourjandi, Meisam Yadollahzadeh Tabari
, Mehdi GolsorkhtabariAmiri
:
Predicting user's movement path in indoor environments using the stacked deep learning method and the fuzzy soft-max classifier. IET Signal Process. 16(5): 546-561 (2022) - 2021
- [j6]Azam Qarehkhani, Mehdi Golsorkhtabaramiri, Hosein Mohamadi, Meisam Yadollahzadeh Tabari
:
Solving target coverage problem in directional sensor networks with ability to adjust sensing range using continuous learning automata. J. Intell. Fuzzy Syst. 41(6): 6831-6844 (2021) - [j5]Meisam Yadollahzadeh Tabari
:
An Stochastic Reward net Model for Performance Analysis of Network layer in Mobile Ad Hoc Network Under the Workload of Misbehvaior Nodes. Wirel. Pers. Commun. 118(2): 1087-1109 (2021) - 2020
- [j4]Arash Mazidi
, Mehdi Golsorkhtabaramiri
, Meisam Yadollahzadeh Tabari
:
An autonomic risk- and penalty-aware resource allocation with probabilistic resource scaling mechanism for multilayer cloud resource provisioning. Int. J. Commun. Syst. 33(7) (2020) - [j3]Arash Mazidi
, Mehdi Golsorkhtabaramiri
, Meisam Yadollahzadeh Tabari
:
Autonomic resource provisioning for multilayer cloud applications with K-nearest neighbor resource scaling and priority-based resource allocation. Softw. Pract. Exp. 50(8): 1600-1625 (2020)
2010 – 2019
- 2017
- [j2]Ali A. Pouyan, Meisam Yadollahzadeh Tabari
:
FPN-SAODV: using fuzzy petri nets for securing AODV routing protocol in mobile Ad hoc network. Int. J. Commun. Syst. 30(1) (2017) - [j1]Meisam Yadollahzadeh Tabari
, Ali A. Pouyan:
Misbehavior analysis of IEEE 802.11 MAC layer in mobile ad hoc network using stochastic reward nets. Int. J. Commun. Syst. 30(16) (2017) - 2012
- [c1]Meisam Yadollahzadeh Tabari
, Hamid Hassanpour
, Ali Pouyan, Saman Saleki:
Proposing a light weight semi-distributed IDS for mobile ad-hoc network based on nodes' mode. IST 2012: 948-953
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