DeepWeeds: A multiclass weed species image dataset for deep learning A Olsen, DA Konovalov, B Philippa, P Ridd, JC Wood, J Johns, W Banks, ... Scientific reports 9 (1), 2058, 2019 | 361 | 2019 |
A new quantum-dot cellular automata full-adder K Navi, R Farazkish, S Sayedsalehi, MR Azghadi Microelectronics Journal 41 (12), 820-826, 2010 | 300 | 2010 |
Internet of Underwater Things and Big Marine Data Analytics—A Comprehensive Survey M Jahanbakht, W Xiang, L Hanzo, M Rahimi Azghadi IEEE Communications Surveys & Tutorials, 2021 | 262 | 2021 |
Five-input majority gate, a new device for quantum-dot cellular automata K Navi, S Sayedsalehi, R Farazkish, MR Azghadi Journal of Computational and Theoretical Nanoscience 7 (8), 1546-1553, 2010 | 259 | 2010 |
A novel design for quantum-dot cellular automata cells and full adders MR Azghadi, O Kavehei, K Navi Journal of Applied Sciences 7 (22), 3460-3468, 2007 | 183* | 2007 |
Hardware implementation of deep network accelerators towards healthcare and biomedical applications MR Azghadi, C Lammie, JK Eshraghian, M Payvand, E Donati, ... IEEE Transactions on Biomedical Circuits and Systems 14 (6), 1138-1159, 2020 | 157 | 2020 |
Spike-based synaptic plasticity in silicon: design, implementation, application, and challenges MR Azghadi, N Iannella, SF Al-Sarawi, G Indiveri, D Abbott Proceedings of the IEEE 102 (5), 717-737, 2014 | 148 | 2014 |
Neuromorphic context-dependent learning framework with fault-tolerant spike routing S Yang, J Wang, B Deng, MR Azghadi, B Linares-Barranco IEEE transactions on neural networks and learning systems 33 (12), 7126-7140, 2021 | 136 | 2021 |
A hybrid cmos-memristor neuromorphic synapse MR Azghadi, B Linares-Barranco, D Abbott, PHW Leong IEEE transactions on biomedical circuits and systems 11 (2), 434-445, 2017 | 136 | 2017 |
Population-Based Optimization Algorithms for Solving the Travelling Salesman Problem MR Bonyadi, MR Azghadi, H Shah-hosseini Traveling Salesman Problem, 1-34, 2008 | 127* | 2008 |
Complementary Metal‐Oxide Semiconductor and Memristive Hardware for Neuromorphic Computing M Rahimi Azghadi, YC Chen, JK Eshraghian, J Chen, CY Lin, ... Advanced Intelligent Systems, 1900189, 2020 | 121 | 2020 |
CerebelluMorphic: Large-Scale Neuromorphic Model and Architecture for Supervised Motor Learning S Yang, J Wang, N Zhang, B Deng, Y Pang, MR Azghadi IEEE transactions on neural networks and learning systems, 2021 | 118 | 2021 |
CORDIC-SNN: On-FPGA STDP learning with izhikevich neurons M Heidarpur, A Ahmadi, M Ahmadi, MR Azghadi IEEE Transactions on Circuits and Systems I: Regular Papers 66 (7), 2651-2661, 2019 | 117 | 2019 |
Low-Power and High-Speed Deep FPGA Inference Engines for Weed Classification at the Edge. C Lammie, A Olsen, T Carrick, MR Azghadi IEEE Access 7, 51171-51184, 2019 | 105 | 2019 |
Automated machine learning for healthcare and clinical notes analysis A Mustafa, M Rahimi Azghadi Computers 10 (2), 24, 2021 | 97 | 2021 |
A novel low-power full-adder cell with new technique in designing logical gates based on static CMOS inverter K Navi, V Foroutan, MR Azghadi, M Maeen, M Ebrahimpour, M Kaveh, ... Microelectronics Journal 40 (10), 1441-1448, 2009 | 97 | 2009 |
Restoring and non-restoring array divider designs in quantum-dot cellular automata S Sayedsalehi, MR Azghadi, S Angizi, K Navi Information sciences 311, 86-101, 2015 | 90 | 2015 |
MemTorch: An open-source simulation framework for memristive deep learning systems C Lammie, W Xiang, B Linares-Barranco, MR Azghadi Neurocomputing 485, 124-133, 2022 | 68 | 2022 |
A novel QCA multiplexer design S Hashemi, MR Azghadi, A Zakerolhosseini 2008 International Symposium on Telecommunications, 692-696, 2008 | 68 | 2008 |
SAM: A Unified Self-Adaptive Multicompartmental Spiking Neuron Model for Learning with Working Memory S Yang, T Gao, J Wang, B Deng, MR Azghadi, T Lei, B Linares-Barranco Frontiers in Neuroscience, 467, 2022 | 66 | 2022 |