Automatic Over the Air Deployment of Improved Machine Learning Models to IoT Devices for Edge Processing
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Updated
Mar 16, 2018 - Objective-C
Automatic Over the Air Deployment of Improved Machine Learning Models to IoT Devices for Edge Processing
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 framework for offloading parts of an Android mobile application to nearby Android mobile devices using Wifi-Direct , edge devices (cloudlets), and remote clouds
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.
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 …
Home Climate Control ESP8266 based edge device firmware
Yocto Project meta layer for EdgeX Foundry Services
Edge Computing using Tensorflow Lite
This repository is a PyTorch implementation of NIPS 2019 Paper "Shallow RNNs: A Method for Accurate Time-series Classification on Tiny Devices"
An end-to-end video analytic demonstration performing video analytics on edge devices and centralized system
Home Climate Control ESP32 based edge device firmware
Detect coronavirus in an automated way in x-ray images using COVID19KIT
A project utilizing transfer learning to create a custom object detection model that is deployed to an edge device.
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.
Masstransit with fanout and direct exchanges
Personal blog polarize.ai of Helmut Hoffer von Ankershoffen
vendor independent TinyML deep learning library, compiler and inference framework microcomputers and micro-controllers
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
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