SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.
-
Updated
Nov 23, 2024 - Python
SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.
[IEEE TCYB 2023] The first large-scale tracking dataset by fusing RGB and Event cameras.
Resources Related to Event-based Vision | Event Cameras | DVS
EVDodgeNet: Deep Dynamic Obstacle Dodging with event cameras
interfaces and algorithms for event based cameras, lidars, and actuators
The Only Calculator App You'll Ever Need.
A unified framework for event-based video. Encoder/transcoder/decoder for ADΔER (Address, Decimation, Δt Event Representation) video streams.
Offical implementation of "Adaptive Smoothing Gradient Learning for Spiking Neural Networks", ICML 2023
Post-synthesis power optimization via dual-Vth cell assignment and gate re-sizing. Scripting in TCL with custom commands written for Synopsys® PrimeTime® and DC Ultra™.
STBP (Spatio Temporal Back Propagation) implemented on SL-Animals-DVS dataset for training Spiking Neural Networks
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
Reconstructing a depth map by from two DAVIS and a controlled laser.
Rust port of https://github.com/MartinNowak96/AEDAT-File-Reader
SLAYER (Spiking Layer Error Reassignment in Time) implemented on SL-Animals-DVS dataset for training Spiking Neural Networks
DECOLLE (Deep Continuous Local Learning) implemented on SL-Animals-DVS dataset for training Spiking Neural Networks
Add a description, image, and links to the dvs topic page so that developers can more easily learn about it.
To associate your repository with the dvs topic, visit your repo's landing page and select "manage topics."