Muhammad Awais

Orcid: 0000-0001-6421-9245

Affiliations:
  • University of Leeds, Faculty of Medicine and Health, School of Psychology, UK
  • University of Bologna, Italy
  • Universiti Teknologi PETRONAS, Department of Electrical and Electronic Engineering, Malaysia


According to our database1, Muhammad Awais authored at least 30 papers between 2015 and 2023.

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

Timeline

Legend:

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Bibliography

2023
Toward Optimal Softcore Carry-aware Approximate Multipliers on Xilinx FPGAs.
ACM Trans. Embed. Comput. Syst., July, 2023

Machine-Learning-Enabled Obesity Level Prediction Through Electronic Health Records.
Comput. Syst. Sci. Eng., 2023

Deep Learning Based Anomaly Detection for Fog-Assisted IoVs Network.
IEEE Access, 2023

2022
Machine Learning and Internet of Things Enabled Monitoring of Post-Surgery Patients: A Pilot Study.
Sensors, 2022

False Data Injection Detection for Phasor Measurement Units.
Sensors, 2022

2021
A Novel Feature Extraction and Fault Detection Technique for the Intelligent Fault Identification of Water Pump Bearings.
Sensors, 2021

Classical Machine Learning Versus Deep Learning for the Older Adults Free-Living Activity Classification.
Sensors, 2021

Review and Implementation of Resilient Public Safety Networks: 5G, IoT, and Emerging Technologies.
IEEE Netw., 2021

Intelligent IoT Framework for Indoor Healthcare Monitoring of Parkinson's Disease Patient.
IEEE J. Sel. Areas Commun., 2021

Challenges and Limitations of Internet of Things Enabled Healthcare in COVID-19.
IEEE Internet Things Mag., 2021

Autonomous Transportation in Emergency Healthcare Services: Framework, Challenges, and Future Work.
IEEE Internet Things Mag., 2021

LSTM-Based Emotion Detection Using Physiological Signals: IoT Framework for Healthcare and Distance Learning in COVID-19.
IEEE Internet Things J., 2021

Novel congestion avoidance scheme for Internet of Drones.
Comput. Commun., 2021

Treating Class Imbalance in Non-Technical Loss Detection: An Exploratory Analysis of a Real Dataset.
IEEE Access, 2021

2020
Establishing effective communications in disaster affected areas and artificial intelligence based detection using social media platform.
Future Gener. Comput. Syst., 2020

Performance Analysis of Different Types of Machine Learning Classifiers for Non-Technical Loss Detection.
IEEE Access, 2020

2019
Physical Activity Classification for Elderly People in Free-Living Conditions.
IEEE J. Biomed. Health Informatics, 2019

An Internet of Things Based Bed-Egress Alerting Paradigm Using Wearable Sensors in Elderly Care Environment.
Sensors, 2019

Diagnosis and monitoring of Alzheimer's patients using classical and deep learning techniques.
Expert Syst. Appl., 2019

A Condition Monitoring System for the Analysis of Bearing Distributed Faults.
Proceedings of the 10th IEEE Annual Ubiquitous Computing, 2019

2017
A Hybrid Approach to Detect Driver Drowsiness Utilizing Physiological Signals to Improve System Performance and Wearability.
Sensors, 2017

Quantitative comparison of motion history image variants for video-based depression assessment.
EURASIP J. Image Video Process., 2017

Mammogram classification using deep learning features.
Proceedings of the 2017 IEEE International Conference on Signal and Image Processing Applications, 2017

Transfer learning for Diabetic Macular Edema (DME) detection on Optical Coherence Tomography (OCT) images.
Proceedings of the 2017 IEEE International Conference on Signal and Image Processing Applications, 2017

Classification of SD-OCT images using a Deep learning approach.
Proceedings of the 2017 IEEE International Conference on Signal and Image Processing Applications, 2017

EEG Brain Connectivity Analysis to Detect Driver Drowsiness Using Coherence.
Proceedings of the 2017 International Conference on Frontiers of Information Technology, 2017

2016
Performance Evaluation of State of the Art Systems for Physical Activity Classification of Older Subjects Using Inertial Sensors in a Real Life Scenario: A Benchmark Study.
Sensors, 2016

Physical activity classification using body-worn inertial sensors in a multi-sensor setup.
Proceedings of the 2nd IEEE International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow, 2016

Physical activity classification meeting daily life conditions.
Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2016 ACM International Symposium on Wearable Computers, 2016

2015
Physical activity classification meets daily life: Review on existing methodologies and open challenges.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015


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