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An ensemble unsupervised spiking neural network for objective recognition

https://doi.org/10.1016/j.neucom.2020.07.109
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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
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Neural transfer learning for assigning diagnosis codes to EMRs
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Fully automated computer-aided diagnosis system for micro calcifications cancer based on improved mammographic image techniques
inferredcites →https://doi.org/10.1016/j.compind.2019.02.001openalex-snapshot
Deep convolutional neural network based planet bearing fault classification
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Deep learning and transfer learning features for plankton classification
inferredcites →https://doi.org/10.1016/j.imavis.2019.04.010openalex-snapshot
Lip reading with Hahn Convolutional Neural Networks
inferredcites →https://doi.org/10.1016/j.jhydrol.2019.05.066openalex-snapshot
An ensemble neural network model for real-time prediction of urban floods
inferredcites →https://doi.org/10.1016/j.knosys.2019.03.012openalex-snapshot
Detection based visual tracking with convolutional neural network
inferredcites →https://doi.org/10.1016/j.neucom.2016.09.044openalex-snapshot
Supervised learning in spiking neural networks with noise-threshold
inferredcites →https://doi.org/10.1016/j.neucom.2018.10.080openalex-snapshot
Interpretation of convolutional neural networks for speech spectrogram regression from intracranial recordings
inferredcites →https://doi.org/10.1016/j.neunet.2014.09.003openalex-snapshot
Deep learning in neural networks: An overview
inferredcites →https://doi.org/10.1016/j.neunet.2014.12.001openalex-snapshot
Adaptive learning rate of SpikeProp based on weight convergence analysis
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/10.1016/j.neunet.2018.11.009openalex-snapshot
Ensemble Neural Networks (ENN): A gradient-free stochastic method
inferredcites →https://doi.org/10.1016/j.neunet.2018.12.002openalex-snapshot
Deep learning in spiking neural networks
inferredcites →https://doi.org/10.1016/j.neuron.2005.12.009openalex-snapshot
Receptive-Field Modification in Rat Visual Cortex Induced by Paired Visual Stimulation and Single-Cell Spiking
inferredcites →https://doi.org/10.1016/s0303-2647(98)00050-1openalex-snapshot
Rate coding versus temporal order coding: a theoretical approach
inferredcites →https://doi.org/10.1038/s41598-017-04075-zopenalex-snapshot
Breast Cancer Multi-classification from Histopathological Images with Structured Deep Learning Model
inferredcites →https://doi.org/10.1073/pnas.1604850113openalex-snapshot
Convolutional networks for fast, energy-efficient neuromorphic computing
inferredcites →https://doi.org/10.1101/829556openalex-snapshot
Toward One-Shot Learning in Neuroscience-Inspired Deep Spiking Neural Networks
inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot
Gradient-based learning applied to document recognition
inferredcites →https://doi.org/10.1109/cicc.2011.6055294openalex-snapshot
A digital neurosynaptic core using embedded crossbar memory with 45pJ per spike in 45nm
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/ijcnn.2016.7727212openalex-snapshot
Unsupervised regenerative learning of hierarchical features in Spiking Deep Networks for object recognition
inferredcites →https://doi.org/10.1109/ijcnn.2016.7727519openalex-snapshot
Breast cancer histopathological image classification using Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/ijcnn.2019.8852380openalex-snapshot
Deep Spiking Neural Network with Spike Count based Learning Rule
inferredcites →https://doi.org/10.1109/tbme.2015.2496264openalex-snapshot
A Dataset for Breast Cancer Histopathological Image Classification
inferredcites →https://doi.org/10.1109/tnano.2013.2250995openalex-snapshot
Immunity to Device Variations in a Spiking Neural Network With Memristive Nanodevices
inferredcites →https://doi.org/10.1109/tnnls.2014.2362542openalex-snapshot
Feedforward Categorization on AER Motion Events Using Cortex-Like Features in a Spiking Neural Network
inferredcites →https://doi.org/10.1109/tnnls.2018.2833077openalex-snapshot
A Highly Effective and Robust Membrane Potential-Driven Supervised Learning Method for Spiking Neurons
inferredcites →https://doi.org/10.1186/1471-2105-8-110openalex-snapshot
Fast automated cell phenotype image classification
inferredcites →https://doi.org/10.1186/s13640-015-0059-4openalex-snapshot
Simplified spiking neural network architecture and STDP learning algorithm applied to image classification
inferredcites →https://doi.org/10.1371/journal.pcbi.1005137openalex-snapshot
Unsupervised Learning in an Ensemble of Spiking Neural Networks Mediated by ITDP
inferredcites →https://doi.org/10.1609/aaai.v32i1.11317openalex-snapshot
A Plasticity-Centric Approach to Train the Non-Differential Spiking Neural Networks
inferredcites →https://doi.org/10.24963/ijcai.2018/229openalex-snapshot
Brain-inspired Balanced Tuning for Spiking Neural Networks
inferredcites →https://doi.org/10.3389/fnins.2013.00178openalex-snapshot
Real-time classification and sensor fusion with a spiking deep belief network
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.2019.00405openalex-snapshot
A Soft-Pruning Method Applied During Training of Spiking Neural Networks for In-memory Computing Applications

What points at this work

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

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inferred← citeshttps://doi.org/10.1007/978-3-031-57919-6_3openalex-snapshot
Recognition of Signal Modulation Pattern Based on Multi-task Self-supervised Learning
inferred← citeshttps://doi.org/10.1007/978-981-96-2432-4_2openalex-snapshot
Advancements in Spiking Neural Networks for Image Recognition: A Review of Research Progress
inferred← citeshttps://doi.org/10.1007/978-981-99-8082-6_40openalex-snapshot
Encrypted-SNN: A Privacy-Preserving Method for Converting Artificial Neural Networks to Spiking Neural Networks
inferred← citeshttps://doi.org/10.1007/s00422-023-00956-xopenalex-snapshot
Efficient multi-scale representation of visual objects using a biologically plausible spike-latency code and winner-take-all inhibition
inferred← citeshttps://doi.org/10.1007/s10827-023-00861-zopenalex-snapshot
Brain-guided manifold transferring to improve the performance of spiking neural networks in image classification
inferred← citeshttps://doi.org/10.1007/s11063-021-10669-6openalex-snapshot
High-Accuracy Spiking Neural Network for Objective Recognition Based on Proportional Attenuating Neuron
inferred← citeshttps://doi.org/10.1007/s13042-021-01410-9openalex-snapshot
A novel federated learning approach based on the confidence of federated Kalman filters
inferred← citeshttps://doi.org/10.1007/s13748-024-00313-4openalex-snapshot
A Deep Convolutional Spiking Neural Network for Embedded Applications
inferred← citeshttps://doi.org/10.1016/j.asoc.2022.109136openalex-snapshot
Dynamic environment prediction on unmanned mobile manipulator robot via ensemble convolutional randomization networks
inferred← citeshttps://doi.org/10.1016/j.comcom.2023.06.006openalex-snapshot
Wi-Fi frame detection via spiking neural networks with memristive synapses
inferred← citeshttps://doi.org/10.1016/j.eswa.2025.129934openalex-snapshot
Relevance-based adaptive differential private spiking neural networks
inferred← citeshttps://doi.org/10.1016/j.neucom.2023.126773openalex-snapshot
Desire backpropagation: A lightweight training algorithm for multi-layer spiking neural networks based on spike-timing-dependent plasticity
inferred← citeshttps://doi.org/10.1016/j.neucom.2024.128535openalex-snapshot
Maximum entropy intrinsic learning for spiking networks towards embodied neuromorphic vision
inferred← citeshttps://doi.org/10.1038/s41598-025-14619-3openalex-snapshot
Temporal single spike coding for effective transfer learning in spiking neural networks
inferred← citeshttps://doi.org/10.1109/access.2022.3179968openalex-snapshot
Spiking Neural Networks: A Survey
inferred← citeshttps://doi.org/10.1109/icoco59262.2023.10397625openalex-snapshot
Performance Evaluation of Attention Mechanism and Spiking Neural Networks on sMRI Data for Suicide Ideation Assessment
inferred← citeshttps://doi.org/10.1109/mcsoc64144.2024.00077openalex-snapshot
EnsembleSTDP: Distributed in-situ Spike Timing Dependent Plasticity Learning in Spiking Neural Networks
inferred← citeshttps://doi.org/10.1109/mind67540.2025.11351541openalex-snapshot
Active Transfer Learning Strategy for Spiking Neural Networks
inferred← citeshttps://doi.org/10.1109/tcad.2022.3213612openalex-snapshot
Spintronic Memristor-Based Binarized Ensemble Convolutional Neural Network Architectures
inferred← citeshttps://doi.org/10.1109/tnnls.2021.3131356openalex-snapshot
HybridSNN: Combining Bio-Machine Strengths by Boosting Adaptive Spiking Neural Networks
inferred← citeshttps://doi.org/10.1109/tro.2024.3508053openalex-snapshot
Applications of Spiking Neural Networks in Visual Place Recognition
inferred← citeshttps://doi.org/10.1109/vlsid68508.2026.00105openalex-snapshot
Energy Efficient Spiking Neural Networks for Temporal Patterns Using EvoSNN-MO
inferred← citeshttps://doi.org/10.1145/3821725.3821740openalex-snapshot
Fusing Binary SNN and Lightweight CNN: An Ensemble Learning Method
inferred← citeshttps://doi.org/10.1155/2022/4242235openalex-snapshot
A Parallel Spiking Neural Network Based on Adaptive Lateral Inhibition Mechanism for Objective Recognition
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Breast Cancer Recognition Using Saliency‐Based Spiking Neural Network
inferred← citeshttps://doi.org/10.1162/neco_a_01499openalex-snapshot
Advancements in Algorithms and Neuromorphic Hardware for Spiking Neural Networks
inferred← citeshttps://doi.org/10.15588/1607-3274-2024-4-8openalex-snapshot
ENSEMBLE OF SIMPLE SPIKING NEURAL NETWORKS AS A CONCEPT DRIFT DETECTOR
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Advancing energy efficiency of spiking neural network accelerator via dynamic predictive early stopping
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Where do pigeons’ choices come from? Transfer Learning in Spiking Neural Networks for Animal Choices in Behavioral Research
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Bio-Inspired Approaches for Deep Learning: Hebbian Learning, Spiking Neural Networks, and Backprop Alternatives
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Lightweight Network Ensemble Architecture for Environmental Perception on the Autonomous System
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Voltage slope guided learning in spiking neural networks
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Spiking Neural Network Based on Multi-Scale Saliency Fusion for Breast Cancer Detection
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Encrypted Spiking Neural Networks Based on Adaptive Differential Privacy Mechanism
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Cardiac Healthcare Digital Twins Supported by Artificial Intelligence-Based Algorithms and Extended Reality—A Systematic Review
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Spiking Neural Networks for Scalable Visual Place Recognition
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