Search Results - "Azghadi, Mostafa Rahimi"

Internet of Underwater Things and Big Marine Data Analytics-A Comprehensive Survey by Jahanbakht, Mohammad, Xiang, Wei, Hanzo, Lajos, Rahimi Azghadi, Mostafa

“…The Internet of Underwater Things (IoUT) is an emerging communication ecosystem developed for connecting underwater objects in maritime and underwater…”
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CORDIC-SNN: On-FPGA STDP Learning With Izhikevich Neurons by Heidarpur, Moslem, Ahmadi, Arash, Ahmadi, Majid, Rahimi Azghadi, Mostafa

“…This paper proposes a neuromorphic platform for on-FPGA online spike timing dependant plasticity (STDP) learning, based on the COordinate Rotation DIgital…”
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Computer vision and deep learning for fish classification in underwater habitats: A survey by Saleh, Alzayat, Sheaves, Marcus, Rahimi Azghadi, Mostafa

“…Marine scientists use remote underwater image and video recording to survey fish species in their natural habitats. This helps them get a step closer towards…”
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Automated Machine Learning for Healthcare and Clinical Notes Analysis by Mustafa, Akram, Rahimi Azghadi, Mostafa

“…Machine learning (ML) has been slowly entering every aspect of our lives and its positive impact has been astonishing. To accelerate embedding ML in more…”
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A Hybrid CMOS-Memristor Neuromorphic Synapse by Rahimi Azghadi, Mostafa, Linares-Barranco, Bernabe, Abbott, Derek, Leong, Philip H. W.

“…Although data processing technology continues to advance at an astonishing rate, computers with brain-like processing capabilities still elude us. It is…”
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Efficient FPGA Implementations of Pair and Triplet-Based STDP for Neuromorphic Architectures by Lammie, Corey, Hamilton, Tara Julia, van Schaik, Andre, Rahimi Azghadi, Mostafa

“…Synaptic plasticity is envisioned to bring about learning and memory in the brain. Various plasticity rules have been proposed, among which…”
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Spike-Based Synaptic Plasticity in Silicon: Design, Implementation, Application, and Challenges by Rahimi Azghadi, Mostafa, Iannella, Nicolangelo, Al-Sarawi, Said F., Indiveri, Giacomo, Abbott, Derek

“…The ability to carry out signal processing, classification, recognition, and computation in artificial spiking neural networks (SNNs) is mediated by their…”
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Weakly supervised underwater fish segmentation using affinity LCFCN by Laradji, Issam H., Saleh, Alzayat, Rodriguez, Pau, Nowrouzezahrai, Derek, Azghadi, Mostafa Rahimi, Vazquez, David

“…Estimating fish body measurements like length, width, and mass has received considerable research due to its potential in boosting productivity in marine and…”
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Design and analysis of efficient QCA reversible adders by Hashemi, Sara, Rahimi Azghadi, Mostafa, Navi, Keivan

“…Quantum-dot cellular automata (QCA) as an emerging nanotechnology are envisioned to overcome the scaling and the heat dissipation issues of the current CMOS…”
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Low-Power and High-Speed Deep FPGA Inference Engines for Weed Classification at the Edge by Lammie, Corey, Olsen, Alex, Carrick, Tony, Rahimi Azghadi, Mostafa

“…Deep neural networks (DNNs) have recently achieved remarkable performance in a myriad of applications, ranging from image recognition to language processing…”
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Complementary Metal‐Oxide Semiconductor and Memristive Hardware for Neuromorphic Computing by Rahimi Azghadi, Mostafa, Chen, Ying-Chen, Eshraghian, Jason K., Chen, Jia, Lin, Chih-Yang, Amirsoleimani, Amirali, Mehonic, Adnan, Kenyon, Anthony J., Fowler, Burt, Lee, Jack C., Chang, Yao-Feng

“…The ever‐increasing processing power demands of digital computers cannot continue to be fulfilled indefinitely unless there is a paradigm shift in computing…”
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How to track and segment fish without human annotations: a self-supervised deep learning approach by Saleh, Alzayat, Sheaves, Marcus, Jerry, Dean, Rahimi Azghadi, Mostafa

“…Tracking fish movements and sizes of fish is crucial to understanding their ecology and behaviour. Knowing where fish migrate, how they interact with their…”
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Modeling and simulating in-memory memristive deep learning systems: An overview of current efforts by Lammie, Corey, Xiang, Wei, Rahimi Azghadi, Mostafa

“…Deep Learning (DL) systems have demonstrated unparalleled performance in many challenging engineering applications. As the complexity of these systems…”
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Spike Timing Dependent Gradient for Direct Training of Fast and Efficient Binarized Spiking Neural Networks by Cai, Zhengyu, Kalatehbali, Hamid Rahimian, Walters, Ben, Rahimi Azghadi, Mostafa, Amirsoleimani, Amirali, Genov, Roman

“…Spiking neural networks (SNNs) are well-suited for neuromorphic hardware due to their biological plausibility and energy efficiency. These networks utilize…”
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A Review of Graphene‐Based Memristive Neuromorphic Devices and Circuits by Walters, Ben, Jacob, Mohan V., Amirsoleimani, Amirali, Rahimi Azghadi, Mostafa

“…As data processing volume increases, the limitations of traditional computers and the need for more efficient computing methods become evident. Neuromorphic…”
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A neuromorphic VLSI design for spike timing and rate based synaptic plasticity by Rahimi Azghadi, Mostafa, Al-Sarawi, Said, Abbott, Derek, Iannella, Nicolangelo

“…Triplet-based Spike Timing Dependent Plasticity (TSTDP) is a powerful synaptic plasticity rule that acts beyond conventional pair-based STDP (PSTDP). Here, the…”
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Tunable low energy, compact and high performance neuromorphic circuit for spike-based synaptic plasticity by Rahimi Azghadi, Mostafa, Iannella, Nicolangelo, Al-Sarawi, Said, Abbott, Derek

“…Cortical circuits in the brain have long been recognised for their information processing capabilities and have been studied both experimentally and…”
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Efficient sparse spiking auto-encoder for reconstruction, denoising and classification by Walters, Ben, Rahimian Kalatehbali, Hamid, Cai, Zhengyu, Genov, Roman, Amirsoleimani, Amirali, Eshraghian, Jason, Rahimi Azghadi, Mostafa

“…Abstract Auto-encoders are capable of performing input reconstruction, denoising, and classification through an encoder-decoder structure. Spiking…”
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Neuromorphic Context-Dependent Learning Framework With Fault-Tolerant Spike Routing by Yang, Shuangming, Wang, Jiang, Deng, Bin, Azghadi, Mostafa Rahimi, Linares-Barranco, Bernabe

“…Neuromorphic computing is a promising technology that realizes computation based on event-based spiking neural networks (SNNs). However, fault-tolerant on-chip…”
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CerebelluMorphic: Large-Scale Neuromorphic Model and Architecture for Supervised Motor Learning by Yang, Shuangming, Wang, Jiang, Zhang, Nan, Deng, Bin, Pang, Yanwei, Azghadi, Mostafa Rahimi

“…The cerebellum plays a vital role in motor learning and control with supervised learning capability, while neuromorphic engineering devises diverse approaches…”
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