Handwritten digit recognition demo
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Updated
May 8, 2018 - C++
Handwritten digit recognition demo
Appdynamics IoT C++ SDK to monitor performance of embedded applications on connected devices
ECSNeT++ is a simulation framework built on OMNeT++ for Distributed Stream Processing applications running on Edge and Cloud computing environments.
SparkFun's Edge Development Board is based around the newest edge technology and is perfect for getting your feet wet with voice and even gesture recognition without relying on 3rd party cloud services.
Complete project is now available at https://github.com/sedgecloud
TensorFlow Lite for Microcontrollers brings deep neural network algorithms to embedded platforms such as NXP’s i.MX RT1050 microcontroller.
Multiplexed-topics on nodelets
Building a custom digital voice assistant without security worries or wireless Internet is possible thanks to machine learning algorithms and powerful embedded hardware.
Offload object detection and ORBSLAM2 simultaneously from android client to servers via multipath.
TinyML stuff done on my Arduino Nano 33 BLE Sense
一个移动端跨平台的gpu+cpu并行计算的cnn框架(A mobile-side cross-platform gpu+cpu parallel computing CNN framework)
Edge analytics is an approach to data collection and analysis in which an automated analytical computation is performed on data at a sensor, network switch or other device instead of waiting for the data to be sent back to a centralised data store.
Remote areas monitoring IoT node: ULP (Energy-harvesting powered) fire detection & alarming system using Fuzzy logic with an edge computing approach for daily temperature logging.
Application Data Distribution in Edge Computing
🤖🚘 A clustering-based, edge-computing, and low-cost framework for completing automatic navigation problems.
Machine Learning and Computer Vision at the Edge for pills counting using ESP32.
Edge+Autodriving demo system.
Edge-SLAM: Edge-Assisted Visual Simultaneous Localization and Mapping
실시간 이미지 처리 모델을 위한 모바일, 클라우드 영상 전송 파이프라인 개발
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