This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.
-
Updated
May 20, 2024 - C++
This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.
The first competitive instance segmentation approach that runs on small edge devices at real-time speeds.
Deep learning gateway on Raspberry Pi and other edge devices
macchina.io EDGE is a powerful C++ and JavaScript SDK for edge devices, multi-service IoT gateways and connected embedded systems.
Slimmable Networks, AutoSlim, and Beyond, ICLR 2019, and ICCV 2019
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation
vendor independent TinyML deep learning library, compiler and inference framework microcomputers and micro-controllers
LFD is a big update upon LFFD. Generally, LFD is a multi-class object detector characterized by lightweight, low inference latency and superior precision. It is for real-world appilcations.
FedERA is a modular and fully customizable open-source FL framework, aiming to address these issues by offering comprehensive support for heterogeneous edge devices and incorporating both standalone and distributed computing. It includes new software modules to enhance usability and promote environ- mental sustainability.
The core runtime engine for Ambianic Edge devices.
Helmut Hoffer von Ankershoffen experimenting with arm64 based NVIDIA Jetson (Nano and AGX Xavier) edge devices running Kubernetes (K8s) for machine learning (ML) including Jupyter Notebooks, TensorFlow Training and TensorFlow Serving using CUDA for smart IoT.
An end-to-end video analytic demonstration performing video analytics on edge devices and centralized system
Real-time speech enhancement mobile app using Nested U-Net
A framework for offloading parts of an Android mobile application to nearby Android mobile devices using Wifi-Direct , edge devices (cloudlets), and remote clouds
Code for paper "EdgeKE: An On-Demand Deep Learning IoT System for Cognitive Big Data on Industrial Edge Devices"
This repository is a PyTorch implementation of NIPS 2019 Paper "Shallow RNNs: A Method for Accurate Time-series Classification on Tiny Devices"
Personal blog polarize.ai of Helmut Hoffer von Ankershoffen
Python library for serverless Federated Learning experiments.
Automatic Over the Air Deployment of Improved Machine Learning Models to IoT Devices for Edge Processing
Add a description, image, and links to the edge-devices topic page so that developers can more easily learn about it.
To associate your repository with the edge-devices topic, visit your repo's landing page and select "manage topics."