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An Improved STBP for Training High-Accuracy and Low-Spike-Count Spiking Neural Networks

https://doi.org/10.23919/date51398.2021.9474151

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s11263-014-0788-3openalex-snapshot

Spiking Deep Convolutional Neural Networks for Energy-Efficient Object Recognition

inferredcites →https://doi.org/10.1016/j.neucom.2016.04.029openalex-snapshot

Bio-inspired unsupervised learning of visual features leads to robust invariant object recognition

inferredcites →https://doi.org/10.1016/j.neunet.2017.12.005openalex-snapshot

STDP-based spiking deep convolutional neural networks for object recognition

inferredcites →https://doi.org/10.1073/pnas.1604850113openalex-snapshot

Convolutional networks for fast, energy-efficient neuromorphic computing

inferredcites →https://doi.org/10.1109/dac18072.2020.9218714openalex-snapshot

A 90nm 103.14 TOPS/W Binary-Weight Spiking Neural Network CMOS ASIC for Real-Time Object Classification

inferredcites →https://doi.org/10.1109/icrc.2016.7738691openalex-snapshot

Conversion of artificial recurrent neural networks to spiking neural networks for low-power neuromorphic hardware

inferredcites →https://doi.org/10.1109/ijcnn.2015.7280696openalex-snapshot

Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing

inferredcites →https://doi.org/10.1109/jssc.2020.2970709openalex-snapshot

Tianjic: A Unified and Scalable Chip Bridging Spike-Based and Continuous Neural Computation

inferredcites →https://doi.org/10.1109/mm.2018.112130359openalex-snapshot

Loihi: A Neuromorphic Manycore Processor with On-Chip Learning

inferredcites →https://doi.org/10.1109/tnnls.2018.2826721openalex-snapshot

First-Spike-Based Visual Categorization Using Reward-Modulated STDP

inferredcites →https://doi.org/10.1142/s0129065720500276openalex-snapshot

Temporal Backpropagation for Spiking Neural Networks with One Spike per Neuron

inferredcites →https://doi.org/10.1162/neco_a_01086openalex-snapshot

SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks

inferredcites →https://doi.org/10.1166/jolpe.2018.1582openalex-snapshot

Power-Accuracy Trade-Offs for Heartbeat Classification on Neural Networks Hardware

inferredcites →https://doi.org/10.1609/aaai.v33i01.33011311openalex-snapshot

Direct Training for Spiking Neural Networks: Faster, Larger, Better

inferredcites →https://doi.org/10.3389/fnins.2016.00508openalex-snapshot

Training Deep Spiking Neural Networks Using Backpropagation

inferredcites →https://doi.org/10.3389/fnins.2017.00682openalex-snapshot

Conversion of Continuous-Valued Deep Networks to Efficient Event-Driven Networks for Image Classification

inferredcites →https://doi.org/10.3389/fnins.2018.00331openalex-snapshot

Spatio-Temporal Backpropagation for Training High-Performance Spiking Neural Networks

inferredcites →https://doi.org/10.3389/fnins.2018.00435openalex-snapshot

Training Deep Spiking Convolutional Neural Networks With STDP-Based Unsupervised Pre-training Followed by Supervised Fine-Tuning

inferredcites →https://doi.org/10.3389/fnins.2019.00095openalex-snapshot

Going Deeper in Spiking Neural Networks: VGG and Residual Architectures

inferredcites →https://doi.org/10.3389/fnins.2020.00119openalex-snapshot

Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures

inferredcites →https://doi.org/10.48550/arxiv.1510.08829openalex-snapshot

Spiking Deep Networks with LIF Neurons

inferredcites →https://doi.org/10.48550/arxiv.1906.00851openalex-snapshot

SpikeGrad: An ANN-equivalent Computation Model for Implementing Backpropagation with Spikes

inferredcites →https://doi.org/10.57702/zp44cu3gopenalex-snapshot

Learning Multiple Layers of Features from Tiny Images

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4854559openalex-extracted

Ternary Spike-Based Neuromorphic Signal Processing System

inferred← citeshttps://doi.org/10.1007/s11063-025-11786-2openalex-snapshot

Spike-Count Reduction Techniques for Low Power Spiking Neural Networks

inferred← citeshttps://doi.org/10.1007/s40747-023-00983-yopenalex-snapshot

BPLC + NOSO: backpropagation of errors based on latency code with neurons that only spike once at most

inferred← citeshttps://doi.org/10.1088/2634-4386/ae0a78openalex-snapshot

STOP: spatiotemporal orthogonal propagation for weight-threshold-leakage synergistic training of deep spiking neural networks

inferred← citeshttps://doi.org/10.1109/aicas54282.2022.9869846openalex-snapshot

An Energy-Efficient Spiking Neural Network for Finger Velocity Decoding for Implantable Brain-Machine Interface

inferred← citeshttps://doi.org/10.1109/icta60488.2023.10364247openalex-snapshot

A Lightweight Integer-STBP On-Chip Learning Method of Spiking Neural Networks For Edge Processors

inferred← citeshttps://doi.org/10.1109/iscas58744.2024.10558378openalex-snapshot

Spiking-HDC: A Spiking Neural Network Processor with HDC Classifier Enabling Transfer Learning

inferred← citeshttps://doi.org/10.1109/iwasi58316.2023.10164354openalex-snapshot

ColibriUAV: An Ultra-Fast, Energy-Efficient Neuromorphic Edge Processing UAV-Platform with Event-Based and Frame-Based Cameras

inferred← citeshttps://doi.org/10.1109/jssc.2025.3603002openalex-snapshot

A 22-nm Residual Spiking Neural Network Chip Based on Sparsity-Adaptive In-Memory Computing and a Spike-Driven Architecture

inferred← citeshttps://doi.org/10.1109/tnnls.2025.3583747openalex-snapshot

Robust Spatiotemporal Prototype Learning for Spiking Neural Networks

inferred← citeshttps://doi.org/10.1109/tsusc.2025.3620000openalex-snapshot

SEOF: Reducing Spikes for Efficient SCNN Accelerators With Approximate Computing

inferred← citeshttps://doi.org/10.1109/tvlsi.2023.3327417openalex-snapshot

A 40-nm 1.89-pJ/SOP Scalable Convolutional Spiking Neural Network Learning Core With On-Chip Spatiotemporal Back-Propagation

inferred← citeshttps://doi.org/10.1109/vlsi-tsa/vlsi-dat57221.2023.10134319openalex-snapshot

Hardware-aware Model Architecture for Ternary Spiking Neural Networks

inferred← citeshttps://doi.org/10.1145/3566097.3567875openalex-snapshot

A Low-Bitwidth Integer-STBP Algorithm for Efficient Training and Inference of Spiking Neural Networks

inferred← citeshttps://doi.org/10.3390/a17040156openalex-snapshot

Spike-Weighted Spiking Neural Network with Spiking Long Short-Term Memory: A Biomimetic Approach to Decoding Brain Signals

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