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Found 5 papers, 3 papers with code
Hybrid Spiking Neural Network Fine-tuning for Hippocampus Segmentation
Over the past decade, artificial neural networks (ANNs) have made tremendous advances, in part due to the increased availability of annotated data.
Spiking Neural Networks for event-based action recognition: A new task to understand their advantage
Spiking Neural Networks (SNN) are characterised by their unique temporal dynamics, but the properties and advantages of such computations are still not well understood.
Zero-shot visual reasoning through probabilistic analogical mapping
Human reasoning is grounded in an ability to identify highly abstract commonalities governing superficially dissimilar visual inputs.
Simple and complex spiking neurons: perspectives and analysis in a simple STDP scenario
From this selection, we make a comparative study of three simple I&F neuron models, namely the LIF, the Quadratic I&F (QIF) and the Exponential I&F (EIF), to understand whether the use of more complex models increases the performance of the system and whether the choice of a neuron model can be directed by the task to be completed.
Keys to Accurate Feature Extraction Using Residual Spiking Neural Networks
Spiking neural networks (SNNs) have become an interesting alternative to conventional artificial neural networks (ANN) thanks to their temporal processing capabilities and energy efficient implementations in neuromorphic hardware.
