M
Mohamed Hisham Jaward
Researcher at Monash University Malaysia Campus
Publications - 32
Citations - 902
Mohamed Hisham Jaward is an academic researcher from Monash University Malaysia Campus. The author has contributed to research in topics: Particle filter & Monte Carlo method. The author has an hindex of 11, co-authored 29 publications receiving 601 citations. Previous affiliations of Mohamed Hisham Jaward include University of Bristol & Monash University.
Papers
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Journal ArticleDOI
A review of hand gesture and sign language recognition techniques
TL;DR: A thorough review of state-of-the-art techniques used in recent hand gesture and sign language recognition research, suitably categorized into different stages: data acquisition, pre-processing, segmentation, feature extraction and classification.
Journal ArticleDOI
Particle filtering-based fault detection in non-linear stochastic systems
TL;DR: A novel particle filtering based approach to fault detection in non- linear stochastic systems is developed here and the effectiveness of this new method is demonstrated through Monte Carlo simulations and the detection performance is compared with that using the extended Kalman filter on a non-linear system.
Proceedings ArticleDOI
Multiple object tracking using particle filters
TL;DR: The proposed particle filter (PF) embeds a data association technique based on the joint probabilistic data association (JPDA) which handles the uncertainty of the measurement origin and is able to cope with partial occlusions and to recover the tracks after temporary loss.
Journal ArticleDOI
A Survey of Security Challenges, Attacks Taxonomy and Advanced Countermeasures in the Internet of Things
Shapla Khanam,Ismail Ahmedy,Mohd Yamani Idna Idris,Mohamed Hisham Jaward,Aznul Qalid Md Sabri +4 more
TL;DR: This study considers and reports on the most advanced security countermeasures within the areas of autonomic, encryption, and learning-based approaches, and uncover security challenges that may be met by the research community regarding security implementation in heterogeneous IoT environment.
Proceedings ArticleDOI
A mobile application of American sign language translation via image processing algorithms
TL;DR: A novel framework comprising established image processing techniques is proposed to recognise images of several sign language gestures and is able to recognize and translate 16 different American Sign Language gestures with an overall accuracy of 97.13%.