🚀🚀🚀 A collection of some awesome public YOLO object detection series projects.
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Updated
May 29, 2024
🚀🚀🚀 A collection of some awesome public YOLO object detection series projects.
A PyTorch implementation of Spiking-YOLOv3. Two branches are provided, based on two common PyTorch implementation of YOLOv3(ultralytics/yolov3 & eriklindernoren/PyTorch-YOLOv3), with support for Spiking-YOLOv3-Tiny at present.
Offical implementation of "Spike-driven Transformer" (NeurIPS2023)
Offical implementation of "Deep Directly-Trained Spiking Neural Networks for Object Detection" (ICCV2023)
🔥🔥🔥A collection of some awesome public SNN(Spiking Neural Network) projects.
A paper list of spiking neural networks, including papers, codes, and related websites. 本仓库收集脉冲神经网络相关的顶会顶刊论文和代码,正在持续更新中。
实现一种多Lora权值集成切换+Zero-Finetune零微调增强的跨模型技术方案,LLM-Base+LLM-X+Alpaca,初期,LLM-Base为Chatglm6B底座模型,LLM-X是LLAMA增强模型。该方案简易高效,目标是使此类语言模型能够低能耗广泛部署,并最终在小模型的基座上发生“智能涌现”,力图最小计算代价达成ChatGPT、GPT4、ChatRWKV等人类友好亲和效果。当前可以满足总结、提问、问答、摘要、改写、评论、扮演等各种需求。
Code for VPRTempo, our temporally encoded spiking neural network for visual place recognition.
PyTorch and Loihi implementation of the Spiking Neural Network for decoding EEG on Neuromorphic Hardware
Leaky Integrate and Fire (LIF) model implementation for FPGA
A supervised learning algorithm of SNN is proposed by using spike sequences with complex spatio-temporal information. We explore an error back-propagation method of SNN based on gradient descent. The chain rule proved mathematically that it is sufficient to update the SNN’s synaptic weights by directly using an optimizer. Utilizing the TensorFlo…
This repository contains all codes necessary to reproduce figures and results reported in Stein, Barbosa et al. (Nature Communications, 2020) from the raw data acquired in human behavioral experiments (data included in the repository), and from the relevant model simulations.
Demo: Spiking Neural Network (SNN) using Generalised Linear Model (GLM)
Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation
Bio-inspired spiking-neural-network framework on an autonomous robot car.
Spiking Neural Network implementation in pure C++ with minimal dependencies
SSTDP is a efficient spiking neural network training framework, which is contributed by Fangxin Liu and Wenbo Zhao.
3D Spiking neural network simulation exploring Spike Timing Dependent Plasticity (STDP)
Bio-inspired neuromorphic cerebellum
Implementation of the paper Keys to Accurate Feature Extraction Using Residual Spiking Neural Networks
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