Hamidur Rahman is a doctoral (PhD) student since November, 2015 in Intelligent Systems group of Innovation, Design and Engineering (IDT) in Mälardalens University. He finished his Licentiate degree in June 2018. The title of his Licentiate Thesis was An Intelligent Non-Contact based Approach for Monitoring Driver’s Cognitive Load.
Hamidur's research interest includes Big data, Machine Learning, Deep Learning, Signal Processing, Image Processing and Computer Vision. He has been working to develop non-contact based system based on camera images/videos using machine learning technology for real life applications such as driver monitoring and personal health care.
A Vision based Indoor Navigation System for Individual with Visual Impairment (May 2020) Mobyen Uddin Ahmed, Mohammed Ghaith Altarabichi, Shahina Begum, Fredrik Ginsberg , Robert Glaes , Magnus Östgren , Hamidur Rahman, Magnus Sörensen International Journal of Artificial Intelligence (IJAI)
Non-contact-based Driver's Cognitive Load Classification using Physiological and Vehicular Parameters (Nov 2019) Hamidur Rahman, Mobyen Uddin Ahmed, Shaibal Barua, Shahina Begum Biomedical Signal Processing and Control (BSPC)
Non-contact Physiological Parameters Extraction using Facial Video considering Illumination, Motion, Movement and Vibration (May 2019) Hamidur Rahman, Mobyen Uddin Ahmed, Shahina Begum IEEE Transactions on Biomedical Engineering (TBME)
Quality Index Analysis on Camera-based R-peak Identification Considering Movements and Light Illumination (Jun 2018) Mobyen Uddin Ahmed, Hamidur Rahman, Shahina Begum 15th International Conference on Wearable, Micro & Nano technologies for Personalized Health (pHealth2018)
Vision-Based Remote Heart Rate Variability Monitoring using Camera (Oct 2017) Hamidur Rahman, Mobyen Uddin Ahmed, Shahina Begum 4th EAI International Conference on IoT Technologies for HealthCare (HealthyIoT'17)
Deep Learning based Person Identification using Facial Images (Oct 2017) Hamidur Rahman, Mobyen Uddin Ahmed, Shahina Begum 4th EAI International Conference on IoT Technologies for HealthCare (HealthyIoT'17)
|HR R-peak detection quality index analysis||finished|
|INVIP: Indoor Navigation for Visual Impairment Persons using Computer Vision and Machine learning||finished|
|SafeDriver: A Real Time Driver's State Monitoring and Prediction System||finished|
|Deep Learning based Eye Tracking and Head Movement Detection||available|
|Remote monitoring of physiological parameters using facial images||available|
|Smart Mirror to monitor Health Status using Biological Signals||available|
|Human Emotion Detection using Deep Learning||in progress|