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Muddasar Naeem
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2020 – today
- 2024
- [j12]Mansoor Jamal, Zaib Ullah
, Muddasar Naeem
A Hybrid Multi-Agent Reinforcement Learning Approach for Spectrum Sharing in Vehicular Networks. Future Internet 16(5): 152 (2024) - 2023
- [j11]Syed Ihtesham Hussain Shah
An AI-empowered infrastructure for risk prevention during medical examination. Expert Syst. Appl. 225: 120048 (2023) - [c13]Patrizia Ribino, Antonio Coronato
Preface to the Proceedings of the 3rd International Workshop on Self-Learning in Intelligent Environments (SeLIE'23). Intelligent Environments (Workshops) 2023: 95-96 - 2022
- [j10]Syed Ihtesham Hussain Shah
Learning and Assessing Optimal Dynamic Treatment Regimes Through Cooperative Imitation Learning. IEEE Access 10: 78148-78158 (2022) - [j9]Mario Ciampi
An intelligent environment for preventing medication errors in home treatment. Expert Syst. Appl. 193: 116434 (2022) - [j8]Muddasar Naeem
An AI-Empowered Home-Infrastructure to Minimize Medication Errors. J. Sens. Actuator Networks 11(1): 13 (2022) - [j7]Muddasar Naeem
Application of Reinforcement Learning and Deep Learning in Multiple-Input and Multiple-Output (MIMO) Systems. Sensors 22(1): 309 (2022) - [j6]Muddasar Naeem
Optimal User Scheduling in Multi Antenna System Using Multi Agent Reinforcement Learning. Sensors 22(21): 8278 (2022) - [c12]Muddasar Naeem, Valeriano Fabris, Antonio Coronato
A RL Based Model for Improving Human Task Management Performance. Intelligent Environments (Workshops) 2022: 258-265 - [c11]Syed Ihtesham Hussain Shah, Antonio Coronato
Inverse Reinforcement Learning Based Approach for Investigating Optimal Dynamic Treatment Regime. Intelligent Environments (Workshops) 2022: 266-276 - 2021
- [j5]Muddasar Naeem
A reinforcement learning and deep learning based intelligent system for the support of impaired patients in home treatment. Expert Syst. Appl. 168: 114285 (2021) - [c10]Antonio Coronato, Muddasar Naeem
Ambient Intelligence for Home Medical Treatment Error Prevention. Intelligent Environments 2021: 1-8 - [c9]Rosamaria Donnici, Antonio Coronato, Muddasar Naeem:
A Self-Learning Autonomous and Intelligent System for the Reduction of Medication Errors in Home Treatments. Intelligent Environments (Workshops) 2021: 156-166 - [c8]Zara Hayat, Aqsa Rahim, Sajid Bashir, Muddasar Naeem:
Self Learning of News Category Using AI Techniques. Intelligent Environments (Workshops) 2021: 167-178 - [c7]Sanam Aamir, Aqsa Rahim, Sajid Bashir, Muddasar Naeem
Prediction of Breast Cancer Using AI-Based Methods. Intelligent Environments (Workshops) 2021: 213-220 - 2020
- [j4]Muddasar Naeem
A Gentle Introduction to Reinforcement Learning and its Application in Different Fields. IEEE Access 8: 209320-209344 (2020) - [j3]Antonio Coronato, Muddasar Naeem
Reinforcement learning for intelligent healthcare applications: A survey. Artif. Intell. Medicine 109: 101964 (2020) - [c6]Muddasar Naeem
A CNN based monitoring system to minimize medication errors during treatment process at home. APPIS 2020: 27:1-27:5 - [c5]Muddasar Naeem, Antonio Coronato
A Reinforcement Learning and IoT based System to Assist Patients with Disabilities. IoTBDS 2020: 491-498
2010 – 2019
- 2019
- [j2]Giovanni Paragliola
Risk management for nuclear medical department using reinforcement learning algorithms. J. Reliab. Intell. Environ. 5(2): 105-113 (2019) - [j1]Muddasar Naeem
A Near Optimal Scheduling Algorithm for Efficient Radio Resource Management in Multi-user MIMO Systems. Wirel. Pers. Commun. 106(3): 1411-1427 (2019) - [c4]Antonio Coronato, Muddasar Naeem
A Reinforcement Learning Based Intelligent System for the Healthcare Treatment Assistance of Patients with Disabilities. I-SPAN 2019: 15-28 - [c3]Muddasar Naeem
Adaptive Treatment Assisting System for Patients Using Machine Learning. SNAMS 2019: 460-465 - 2018
- [c2]Giovanni Paragliola
A Reinforcement Learning-Based Approach for the Risk Management of e-Health Environments: A Case Study. SITIS 2018: 711-716 - 2015
- [c1]Muddasar Naeem
Modified Leakage Based User Selection for MU-MIMO Systems. FIT 2015: 320-323
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last updated on 2024-10-07 21:22 CEST by the dblp team
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