Spiking Neural Networks for Computational Intelligence: An Overview (original) (raw)

Exploring Optimized Spiking Neural Network Architectures for Classification Tasks on Embedded Platforms

tehreem syed

Sensors, 2021

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Spiking Neural Networks and Their Applications: A Review

Ngan Le

Brain Sciences

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A Short Survey of the Development and Applications of Spiking Neural Networks of High Biological Plausibility

Vasile Manta

Buletinul Institutului Politehnic din Iaşi, 2022

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Can Deep Neural Networks be Converted to Ultra Low-Latency Spiking Neural Networks?

Gourav Datta

2022 Design, Automation & Test in Europe Conference & Exhibition (DATE)

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Toward Scalable, Efficient, and Accurate Deep Spiking Neural Networks With Backward Residual Connections, Stochastic Softmax, and Hybridization

priyadarshini panda

Frontiers in Neuroscience, 2020

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Accurate and Energy-Efficient Classification with Spiking Random Neural Network: Corrected and Expanded Version

Erol Gelenbe

Probability in the Engineering and Informational Sciences, 2019

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Fast-Classifying, High-Accuracy Spiking Deep Networks Through Weight and Threshold Balancing

Peter Diehl

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Accurate, Energy-Efficient Classification with Spiking Random Neural Network

Erol Gelenbe

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Training Deep Spiking Neural Networks

Giedrius Burachas

2020

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Training Energy-Efficient Deep Spiking Neural Networks with Single-Spike Hybrid Input Encoding

Gourav Datta

2021 International Joint Conference on Neural Networks (IJCNN), 2021

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Temporal-Coded Deep Spiking Neural Network with Easy Training and Robust Performance

Shibo Zhou

2021

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Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation

priyadarshini panda

ArXiv, 2020

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SpikeConverter: An Efficient Conversion Framework Zipping the Gap between Artificial Neural Networks and Spiking Neural Networks

yongbiao chen

Proceedings of the AAAI Conference on Artificial Intelligence

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A Spike in Performance: Training Hybrid-Spiking Neural Networks with Quantized Activation Functions

Iraneide Silva

ArXiv, 2020

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Computing with Spiking Neuron Networks A Review

falah ahmed

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Acceleration of spiking neural networks in emerging multi-core and GPU architectures

Melissa Smith

Parallel & Distributed …, 2010

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An Optimized Deep Spiking Neural Network Architecture Without Gradients

André van Schaik

IEEE Access

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SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks With at Most One Spike per Neuron

Abbas Nowzari-Dalini

Frontiers in Neuroscience

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Neural Architecture Search for Spiking Neural Networks

priyadarshini panda

2022

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Explicitly Trained Spiking Sparsity in Spiking Neural Networks with Backpropagation

Jason Allred

ArXiv, 2020

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Emerging applications of Deep Learning and Spiking ANN

Lazaros Iliadis

Neural Computing and Applications

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Towards Biologically-Plausible Neuron Models and Firing Rates in High-Performance Deep Spiking Neural Networks

Steve Furber

International Conference on Neuromorphic Systems 2021, 2021

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A novel and efficient classifier using spiking neural network

Joshua Arul Kumar R

The Journal of Supercomputing, 2019

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Effective Conversion of a Convolutional Neural Network into a Spiking Neural Network for Image Recognition Tasks

HUYNH CONG VIET NGU

Applied Sciences

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A Fully Spiking Hybrid Neural Network for Energy-Efficient Object Detection

Biswadeep Chakraborty

IEEE Transactions on Image Processing

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Robustness of spiking Deep Belief Networks to noise and reduced bit precision of neuro-inspired hardware platforms

Steve Furber

Frontiers in Neuroscience, 2015

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Rate Coding Or Direct Coding: Which One Is Better For Accurate, Robust, And Energy-Efficient Spiking Neural Networks?

priyadarshini panda

ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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DS4NN: Direct training of deep spiking neural networks with single spike-based temporal coding

maryam mirsadeghi

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[Re] Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks

Laura Edmondson

2021

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Hardware Spiking Neural Networks: Slow Tasks Resilient Learning with Longer Term-Memory Bits

Charly Meyer

2019 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2019

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Challenges for large-scale implementations of spiking neural networks on FPGAs

Jim Harkin

Neurocomputing, 2007

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A Power-Efficient Binary-Weight Spiking Neural Network Architecture for Real-Time Object Classification

PY Chuang

arXiv (Cornell University), 2020

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Towards Energy-Efficient, Low-Latency and Accurate Spiking LSTMs

Gourav Datta

arXiv (Cornell University), 2022

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