Characterization study repository for model compression method: pruning
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Updated
May 28, 2024 - Python
Characterization study repository for model compression method: pruning
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.
This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.
macchina.io EDGE is a powerful C++ and JavaScript SDK for edge devices, multi-service IoT gateways and connected embedded systems.
Deploy a secure, infinitely-scalable API for use in our workflow, accompanied by SDKs for use in working with common deployment devices.
Real-time speech enhancement mobile app using Nested U-Net
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation
Code for paper "EdgeKE: An On-Demand Deep Learning IoT System for Cognitive Big Data on Industrial Edge Devices"
Decentralized and Privacy-Preserving Machine Learning: Exploring the Power of Federated Learning.
The core runtime engine for Ambianic Edge devices.
Python library for serverless Federated Learning experiments.
Slimmable Networks, AutoSlim, and Beyond, ICLR 2019, and ICCV 2019
Resource Efficient Federated Learning (Testbed Implementation)
Deep learning gateway on Raspberry Pi and other edge devices
The first competitive instance segmentation approach that runs on small edge devices at real-time speeds.
vendor independent TinyML deep learning library, compiler and inference framework microcomputers and micro-controllers
Personal blog polarize.ai of Helmut Hoffer von Ankershoffen
Masstransit with fanout and direct exchanges
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.
A project utilizing transfer learning to create a custom object detection model that is deployed to an edge device.
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