Md Zia Uddin, PhD, SM-IEEE
Md Zia Uddin, PhD, SM-IEEE
Research Scientist, Software and Service Innovation Department, SINTEF Digital, Oslo, Norway
Verified email at - Homepage
Cited by
Cited by
A robust human activity recognition system using smartphone sensors and deep learning
MM Hassan, MZ Uddin, A Mohamed, A Almogren
Future Generation Computer Systems 81, 307-313, 2018
Depth video-based human activity recognition system using translation and scaling invariant features for life logging at smart home
A Jalal, MZ Uddin, TS Kim
IEEE Transactions on Consumer Electronics 58 (3), 863-871, 2012
Human emotion recognition using deep belief network architecture
MM Hassan, MGR Alam, MZ Uddin, S Huda, A Almogren, G Fortino
Information Fusion 51, 10-18, 2019
Autonomic computation offloading in mobile edge for IoT applications
MGR Alam, MM Hassan, MZI Uddin, A Almogren, G Fortino
Future Generation Computer Systems 90, 149-157, 2019
Facial expression recognition utilizing local direction-based robust features and deep belief network
MZ Uddin, MM Hassan, A Almogren, A Alamri, M Alrubaian, G Fortino
IEEE Access 5, 4525-4536, 2017
An enhanced independent component-based human facial expression recognition from video
MZ Uddin, JJ Lee, TS Kim
IEEE Transactions on Consumer Electronics 55 (4), 2216-2224, 2009
Recognition of human home activities via depth silhouettes and ℜ transformation for Smart Homes
A Jalal, MZ Uddin, JT Kim, TS Kim
Indoor and Built Environment 21 (1), 184-190, 2012
Ambient sensors for elderly care and independent living: a survey
M Uddin, W Khaksar, J Torresen
Sensors 18 (7), 2027, 2018
A wearable sensor-based activity prediction system to facilitate edge computing in smart healthcare system
MZ Uddin
Journal of Parallel and Distributed Computing 123, 46-53, 2019
A body sensor data fusion and deep recurrent neural network-based behavior recognition approach for robust healthcare
MZ Uddin, MM Hassan, A Alsanad, C Savaglio
Information Fusion 55, 105-115, 2020
Human activity recognition using body joint‐angle features and hidden Markov model
MZ Uddin, ND Thang, JT Kim, TS Kim
Etri Journal 33 (4), 569-579, 2011
Facial expression recognition using salient features and convolutional neural network
MZ Uddin, W Khaksar, J Torresen
IEEE Access 5, 26146-26161, 2017
Independent shape component-based human activity recognition via Hidden Markov Model
MZ Uddin, JJ Lee, TS Kim
Applied Intelligence 33 (2), 193-206, 2010
Human activity recognition from body sensor data using deep learning
MM Hassan, S Huda, MZ Uddin, A Almogren, M Alrubaian
Journal of medical systems 42 (6), 1-8, 2018
A facial expression recognition system using robust face features from depth videos and deep learning
MZ Uddin, MM Hassan, A Almogren, M Zuair, G Fortino, J Torresen
Computers & Electrical Engineering 63, 114-125, 2017
Daily Human Activity Recognition Using Depth Silhouettes and Transformation for Smart Home
A Jalal, MZ Uddin, JT Kim, TS Kim
International Conference on Smart Homes and Health Telematics, 25-32, 2011
Activity recognition for cognitive assistance using body sensors data and deep convolutional neural network
MZ Uddin, MM Hassan
IEEE Sensors Journal 19 (19), 8413-8419, 2018
Classification of recurrence plots’ distance matrices with a convolutional neural network for activity recognition
E Garcia-Ceja, MZ Uddin, J Torresen
Procedia computer science 130, 157-163, 2018
A depth camera-based human activity recognition via deep learning recurrent neural network for health and social care services
SU Park, JH Park, MA Al-Masni, MA Al-Antari, MZ Uddin, TS Kim
Procedia Computer Science 100, 78-84, 2016
Video-based indoor human gait recognition using depth imaging and hidden Markov model: a smart system for smart home
M Zia Uddin, TS Kim, JT Kim
Indoor and built environment 20 (1), 120-128, 2011
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