This page highlights Master’s theses supervised by Dr. Fadi Al Machot, covering topics like applied machine learning, deep learning, robotics, and smart systems. Completed and in-progress projects are listed with thesis titles, and student names.
2025
Siyi Hu, Hand-Based Micro-Activity Recognition Using Wearable Devices, Norwegian University of Life Sciences
2024
Kim Næss Kynningsrud, Evaluating the Impact of Similarity Measures on Transfer Learning in Economic Time Series Analysis, Norwegian University of Life Sciences
Ulrik Egge Husby, Exploring Breast Cancer Diagnosis: A Study of SHAP and LIME in XAI-Driven Medical Imaging, Norwegian University of Life Sciences
Sushant Kumar Srivastava, Semantic Enhancements in Image Captioning: Leveraging Neural Networks to Improve BLIP and GPT-2, Norwegian University of Life Sciences
Eljar Alihosseinzadeh, Siamese Networks for Telecommunication Customer Churn Data in a Few-Shot Learning Context, Norwegian University of Life Sciences
Roy Erling Granheim, Enhancing Exercise Recognition: Integrating Advanced Deep Learning Models for Human Activity Recognition, Norwegian University of Life Sciences
2023
Jorge Eduardo Hermoso Valle, Safety improvement in rock climbing through AI-powered computer vision system by identifying human fault, Norwegian University of Life Sciences
Sigrid Knag, Seagrass and Seaweed Detection Approaches Using Remote Sensing and Google Earth Engine: A Comparative Analysis of Different Machine Learning Techniques , Norwegian University of Life Sciences
Ole Gilje Gunnarshaug , ECG-based Human Emotion Recognition Using Generative Models, Norwegian University of Life Sciences