Adnan Zahid

Orcid: 0000-0001-5364-6057

According to our database1, Adnan Zahid authored at least 15 papers between 2020 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
A Novel Heteromorphic Ensemble Algorithm for Hand Pose Recognition.
Symmetry, February, 2023

An Intelligent Implementation of Multi-Sensing Data Fusion With Neuromorphic Computing for Human Activity Recognition.
IEEE Internet Things J., January, 2023

Quantum for 6G communication: A perspective.
IET Quantum Commun., 2023

2022
Intrusion Detection Framework for the Internet of Things Using a Dense Random Neural Network.
IEEE Trans. Ind. Informatics, 2022

Portable and Feasible Device to Evaluate the Technique of Swimming Practitioners.
IEEE Access, 2022

2021
Public Perception of the Fifth Generation of Cellular Networks (5G) on Social Media.
Frontiers Big Data, 2021

Data Fusion for Human Activity Recognition Based on RF Sensing and IMU Sensor.
Proceedings of the Body Area Networks. Smart IoT and Big Data for Intelligent Health Management, 2021

Detecting Alzheimer's Disease Using Machine Learning Methods.
Proceedings of the Body Area Networks. Smart IoT and Big Data for Intelligent Health Management, 2021

2020
Hardware-Based Hopfield Neuromorphic Computing for Fall Detection.
Sensors, 2020

An Intelligent Non-Invasive Real-Time Human Activity Recognition System for Next-Generation Healthcare.
Sensors, 2020

Detection of Atrial Fibrillation Using a Machine Learning Approach.
Inf., 2020

An Overview of Neuromorphic Computing for Artificial Intelligence Enabled Hardware-Based Hopfield Neural Network.
IEEE Access, 2020

Precision Techniques and Agriculture 4.0 Technologies to Promote Sustainability in the Coffee Sector: State of the Art, Challenges and Future Trends.
IEEE Access, 2020

Link Between Sustainability and Industry 4.0: Trends, Challenges and New Perspectives.
IEEE Access, 2020

Machine Learning Driven Method for Indoor Positioning Using Inertial Measurement Unit.
Proceedings of the 2020 International Conference on UK-China Emerging Technologies, 2020


  Loading...