Library for Drone Autonomy
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Updated
Nov 12, 2017 - Python
Library for Drone Autonomy
Python tools to process and visualize address-event data from dynamic vision sensors such as DVS128
Machine Learning tools for Dynamic Vision Sensors such as DVS128
Code for "Convolutional spiking neural networks (SNN) for spatio-temporal feature extraction" paper
Implementation of "Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks" by Fang et al. (2020)
Multidigraph learning (MDGL) for training recurrent spiking neural networks
ANN to SNN conversion on land cover and land use classification problem for increased energy efficiency.
a (simplistic) neuromimetic retina model based on open hardware such as the raspberry π
Pure python implementation of SNN
Useful tools to compress and decompress AEDAT files in Python
[CCS'22] Backdoor Attacks on Spiking NNs and Neuromorphic Datasets
Metrics for spiking neural networks based on torchmetrics
PyTorch implementation of DynapSE neural model
Function generation from a Sum of Oscillator Signals
Bio-inspired neuromorphic cerebellum
Runs networkx graphs representing spiking neural networks of LIF-neurons on lava-nc or networkx.
PyTorch helper module to translate to and from NIR
Emulation of event camera data using standard RGB images
Learn about the Neumorphic engineering process of creating large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures.
A series of simulation codes used to emulate quantum-like networks in the simulation of emergent adaptive behavior, such as network synchronization, and relate the nature of the coupled harmonic oscillators with non-local behavior and chimera states in systems of quantum particles. Coding Used is based on mathematical modelling of transport in q…
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