M
Mahmoud Masadeh
Researcher at Yarmouk University
Publications - 34
Citations - 343
Mahmoud Masadeh is an academic researcher from Yarmouk University. The author has contributed to research in topics: Computer science & Image processing. The author has an hindex of 7, co-authored 25 publications receiving 105 citations. Previous affiliations of Mahmoud Masadeh include Concordia University & Delft University of Technology.
Papers
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Journal ArticleDOI
Sounds and acoustic emission-based early fault diagnosis of induction motor: A review study:
Omar AlShorman,Fahad Alkahatni,Mahmoud Masadeh,Muhammad Irfan,Adam Glowacz,Faisal Althobiani,J. Kozik,W. Głowacz +7 more
TL;DR: In this article, condition-based maintenance and fault diagnosis of rotating machinery (RM) has a vital role in the modern industrial world, however, the remaining useful life (RUL) of machiner...
Journal ArticleDOI
Frontal lobe real-time EEG analysis using machine learning techniques for mental stress detection.
Omar AlShorman,Mahmoud Masadeh,Belal Bin Heyat,Faijan Akhtar,Hossam Almahasneh,Ghulam Md Ashraf,Athanasios Alexiou +6 more
TL;DR: The frontal lobes EEG spectrum analysis is applied to detect mental stress and has low complexity, high accuracy, simple and easy to use, no over fitting, and it could be used as a real-time and continuous monitoring technique for medical applications.
Proceedings ArticleDOI
Comparative Study of Approximate Multipliers
TL;DR: In this article, the authors identify three decisions for design and evaluation of approximate multiplier circuits: (1) the type of approximate full adder (FA) used to construct the multiplier, (2) the architecture, i.e., array or tree, of the multiplier and (3) the placement of sub-modules of approximate and exact multipliers in the target multiplier module.
Journal ArticleDOI
Input-Conscious Approximate Multiply-Accumulate (MAC) Unit for Energy-Efficiency
TL;DR: A novel FPGA implementation for input-aware energy-efficient 8-bit approximate MAC (AxMAC) unit that reduces its power consumption by performing multiplication operation approximately, or approximating the input operands then replacing multiplication by a simple shift operation is presented.
Proceedings ArticleDOI
A Survey on Deep Learning Classification Algorithms for Motor Imagery
TL;DR: In this paper, the authors reviewed trends and approaches of deep learning algorithms for motor based on previously published papers indexed in Web of Science and screened thirty-six research papers of the motor imagery classification using deep learning methods in the period between 2010 and 2020.