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A Deep Convolutional Spiking Neural Network for embedded applications
Deep neural networks (DNNs) have received a great deal of interest in solving everyday tasks in recent years. However, their computational and energy...
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CIRM-SNN: Certainty Interval Reset Mechanism Spiking Neuron for Enabling High Accuracy Spiking Neural Network
Spiking neural network (SNN) based on sparse trigger and event-driven information processing has the advantages of ultra-low power consumption and...
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Ebola optimization based spiking neural network for automatic hate speech recognition
In this paper, efficient machine learning technique is introduced to develop efficient machine learning model for hate speech recognition from the...
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Spatial spiking neural network for classification of EEG signals for concealed information test
In the field of neuroscience, a significant challenge lies in extracting essential features from biological signals like Electroencephalography...
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Investigation and mitigation of Mott neuronal oscillation fluctuation in spiking neural network
Mott devices, featuring low hardware cost and high energy efficiency, have been demonstrated as a key oscillatory element in artificial neurons to...
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Research Progress of spiking neural network in image classification: a review
Spiking neural network (SNN) is a new generation of artificial neural networks (ANNs), which is more analogous with the brain. It has been widely...
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An efficient pruning and fine-tuning method for deep spiking neural network
Spiking Neural Networks (SNNs) demonstrate low hardware and power consumption due to their inherent sparse spike-based computing characteristics,...
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Multi-level brain-guided fusion to reinforce spiking neural network in image classification
Spiking Neural Networks (SNNs) can be a suitable alternative to deep artificial neural networks due to efficient computation and low-power...
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Improved top-down attention phasmatodea population spiking neural network based multi crop recommendation framework
Modern agriculture refers to the contemporary practices, technologies and methods used in food production to meet the growing global demand for...
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Spiking Reservoir Neural Network for Time Series Classification
Brain-inspired reservoir computing methods attracted a great attention due to their reduced computation complexity by using fixed internal synaptic...
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CLSTM-SNP: Convolutional Neural Network to Enhance Spiking Neural P Systems for Named Entity Recognition Based on Long Short-Term Memory Network
Membrane computing is a type of parallel computing system (generally called P system) abstracted from information exchange mechanisms in biological...
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Hybrid spiking neural network for sleep electroencephalogram signals
Sleep staging is important for assessing sleep quality. So far, many scholars have tried to achieve automatic sleep staging by using neural networks....
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A Novel Unsupervised Spatial–Temporal Learning Mechanism in a Bio-inspired Spiking Neural Network
Bio-inspired computing is a powerful platform that develops intelligent machines based on principles of the behavioral and functional mechanisms of...
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Spiking Equilibrium Convolutional Neural Network for Spatial Urban Ontology
Urban analysis uses new data integration with computational methods to gain insight into urban methodologies. But the challenge is how to populate...
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Biomimetic oculomotor control with spiking neural networks
Spiking neural networks (SNNs) are comprised of artificial neurons that, like their biological counterparts, communicate via electrical spikes. SNNs...
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A revolutionary approach to use convolutional spiking neural networks for robust intrusion detection
In an era dominated by network connectivity, the reliance on robust and secure networks has become paramount. With the advent of 5G and the Internet...
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Spike-EFI: Spiking Neural Network for Event-Based Video Frame Interpolation
In order to model complex motions between video frames more accurately, many video frame interpolation methods have introduced event cameras to...
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Spatiotemporal Backpropagation based on Channel Reward for Training High-Precision Spiking Neural Network
Spiking neural network (SNN) has attracted much attention due to its spatial–temporal information processing ability and high biological reliability....
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Prediction and assessment of credit risk using an adaptive Binarized spiking marine predators’ neural network in financial sector
The rapid advancement of technologies has pushed for additional enhancements to banking and other credit platforms. While assisting small and medium...
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FPGA-based small-world spiking neural network with anti-interference ability under external noise
Neuromorphic hardware has become hotspot in the field of brain-like computing due to its advantages. However, the presence of external noise imposes...
