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Mostafa Rahimi Azghadi
Researcher at James Cook University
Publications - 97
Citations - 2401
Mostafa Rahimi Azghadi is an academic researcher from James Cook University. The author has contributed to research in topics: Computer science & Neuromorphic engineering. The author has an hindex of 20, co-authored 69 publications receiving 1422 citations. Previous affiliations of Mostafa Rahimi Azghadi include Shahid Beheshti University & University of Adelaide.
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Journal ArticleDOI
Five-Input Majority Gate, a New Device for Quantum-Dot Cellular Automata
TL;DR: Simulation results demonstrate that the proposed design of majority gates and Full-Adder resulted in significant improvements in designing logical circuits.
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DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning.
Alex Olsen,Dmitry A. Konovalov,Bronson Philippa,Peter V. Ridd,Jake C. Wood,Jamie Johns,Wesley Banks,Benjamin Girgenti,O.P. Kenny,James Whinney,Brendan Calvert,Mostafa Rahimi Azghadi,Ronald D. White +12 more
TL;DR: The DeepWeeds dataset as mentioned in this paper consists of 17,509 labelled images of eight nationally significant weed species native to eight locations across northern Australia and achieved an average classification accuracy of 95.1% and 95.7%, respectively.
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Internet of Underwater Things and Big Marine Data Analytics—A Comprehensive Survey
TL;DR: The IoUT, BMD, and their synthesis are comprehensively surveyed to inspire researchers, engineers, data scientists, and governmental bodies to further progress the field, to develop new tools and techniques, as well as to make informed decisions and set regulations related to the maritime and underwater environments around the world.
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A Novel Design for Quantum-dot Cellular Automata Cells and Full Adders
TL;DR: In this article, the hardware requirements for a QCA design can be reduced and circuits can be simpler in level and gate counts, by applying these items, and the reduction method by using new proposed item, decreases gate counts and levels in comparison to the other previous methods.
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Spike-Based Synaptic Plasticity in Silicon: Design, Implementation, Application, and Challenges
TL;DR: In this article, the authors describe analog very large-scale integration (VLSI) circuit implementations of multiple synaptic plasticity rules, ranging from phenomenological ones (e.g., based on spike timing, mean firing rates, or both) to biophysically realistic ones.