Detect coronavirus in an automated way in x-ray images using COVID19KIT
-
Updated
Feb 13, 2021 - Java
Detect coronavirus in an automated way in x-ray images using COVID19KIT
Masstransit with fanout and direct exchanges
Deploy a secure, infinitely-scalable API for use in our workflow, accompanied by SDKs for use in working with common deployment devices.
Characterization study repository for pruning, a popular way to compress a DL model. this repo also investigates optimal sparse tensor layouts for pruned nets
Resource Efficient Federated Learning (Testbed Implementation)
Oct 12th @ in5 - Hands-on Internet Of Things workshop with Etisalat Digital & PTC. At this session, we’ll take you step by step over the process of creating a modular IoT solution using the Etisalat Thingworx Platform to monitor weather conditions at various locations. We’ll show you how to sync data from edge devices and sensors onto the cloud …
A framework for offloading parts of an Android mobile application to nearby Android mobile devices using Wifi-Direct , edge devices (cloudlets), and remote clouds
Decentralized and Privacy-Preserving Machine Learning: Exploring the Power of Federated Learning.
TensorRT optimises any Deep Learning model by not only making it lightweight but also by accelerating its inference speed with an idea to extract every ounce of performance from the model, making it perfect to be deployed at the edge. This repository helps you convert any Deep Learning model from TensorFlow to TensorRT!
A project utilizing transfer learning to create a custom object detection model that is deployed to an edge device.
Home Climate Control ESP8266 based edge device firmware
Personal blog polarize.ai of Helmut Hoffer von Ankershoffen
An end-to-end video analytic demonstration performing video analytics on edge devices and centralized system
Edge Computing using Tensorflow Lite
Home Climate Control ESP32 based edge device firmware
Yocto Project meta layer for EdgeX Foundry Services
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"
Python library for serverless Federated Learning experiments.
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."