Successfully Defended Master's Thesis 🎉
A photo with the jury committeeI am thrilled to announce that I have successfully defended the my master’s thesis. My thesis explores the application of Human Activity Recognition (HAR) in the context of physical rehabilitation exercises, aiming to provide real-time feedback and assessment. Here are some key aspects of my research:
Objective: The research investigates various machine learning and deep learning techniques, including transfer learning and attention models, to accurately recognize and evaluate physical movements. 🏋️♂️
Methodology: By utilizing Kinect and RGB cameras, the study ensures accessibility and cost-effectiveness, making advanced rehabilitation technologies more widely available. 📷
Findings: Through a comparative study of machine learning algorithms, a case study on a newly developed framework for assessing rehabilitation exercises, and an analysis of CNN and RNN algorithms across multiple datasets, the thesis offers comprehensive insights into the effectiveness of different approaches. 📊
Contributions: Additionally, the work includes a study on transfer learning and model fusion techniques to enhance HAR performance. The results contribute to the advancement of real-time monitoring systems, providing valuable support for patients and healthcare professionals in the rehabilitation process. 🚀
I would like to express my gratitude to my supervisors, Assoc. Prof. Ayman Ezzat, Dr. Amr Ghoniem, and Dr. Laila Abdelhamid, for their guidance and support throughout this journey. The Pre-defense seminar was held at Helwan University - Faculty of Computers and Artificial Intelligence (FCAI), located in Ain Helwan, Helwan, Cairo 11795. 🎓
Under Supervision of :
- Assoc. Prof. Ayman Ezzat
- Dr. Amr Ghoniem
- Dr. Laila Abdelhamid
Jury Members :
- Assoc. Prof. Ayman Ezzat (Supervisor and Judge)
- Prof. Doaa Elzanfaly (Internal Judge)
- Prof. Ammar Mohamed (External Judge)
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