EfficientFormerV2 [ICCV 2023] & EfficientFormer [NeurIPs 2022]

开源移动端快速视频人脸跟踪-移动端150FPS+

PeleeNet: An efficient DenseNet architecture for mobile devices

Official code (Tensorflow) for paper "Fast and Efficient Image Quality Enhancement via Desubpixel Convolutional Neural Networks"

CK repository with components and automation actions to enable portable workflows across diverse platforms including Linux, Windows, MacOS and Android. It includes software detection plugins and meta packages (code, data sets, models, scripts, etc) with the possibility of multiple versions to co-exist in a user or system environment.

PeleeNet in PyTorch

Collective Knowledge crowd-tuning extension to let users crowdsource their experiments (using portable Collective Knowledge workflows) such as performance benchmarking, auto tuning and machine learning across diverse platforms with Linux, Windows, MacOS and Android provided by volunteers. Demo of DNN crowd-benchmarking and crowd-tuning:

An NPM package written in React used to preview mobile devices. Especially helpful when used in combination with a CMS like Sanity.

Crowdsourcing video experiments (such as collaborative benchmarking and optimization of DNN algorithms) using Collective Knowledge Framework across diverse Android devices provided by volunteers. Results are continuously aggregated in the open repository:

Android application to participate in experiment crowdsourcing (such as workload crowd-benchmarking and crowd-tuning) using Collective Knowledge Framework and open repositories of knowledge:

A collection of awesome framework, libraries, learning tutorials, videos, webcasts, technical resources and cool stuff about iOS Security.

Public scenarios to crowdsource experiments (such as DNN crowd-benchmarking and crowd-tuning) using Collective Knowledge Framework across diverse mobile devices provided by volunteers. Results are continuously aggregated at the open repository of knowledge:

Collective Knowledge workflow for ARM's workload automation tool: an open framework for gathering and sharing knowledge about system design and optimization using real-world workloads.

TransferCL: an open framework for transfer learning on mobile device

This learning path provides system administrators with a comprehensive method for studying the skills tested in the CompTIA A+ (220-1001 and 220-1002) exams. It includes in-depth courses teaching skills from each exam domain and provides insights into resources you can use to prepare for the exam.

Federated Learning (FL) is a collaborative machine learning approach that enables decentralized data processing. Instead of collecting and storing data in a central server, FL trains machine learning models directly on devices or servers where the data resides, enhancing privacy and security.

Bespoke OTA service for Planet Computers Ltd, supported by cloud-native technology.

🏄 A Lightweight Web Browser-based Machine Learning Framework

Detect device is iOS or Android. 检测是iOS设备还是安卓设备。

This standard outlines the security requirements required to protect your organisational data and financial assets

Utility for fetching mobile device(s) name(s). It uses DeviceSpecifications and a Google Programmable Search Engine to fetch the information based on provided model code(s).

Playwright device descriptors catalog (mobile/destkop, viewport, screen size) for browser emulation

💡 Explore innovative code and prototypes in this experimental sandbox inspired by Samsung, perfect for idea generation and technical experimentation.

Federated learning testbed for real-world mobile devices

No description provided.

A static website of a mobile devices store

This project explores user authentication on mobile devices through typing patterns, leveraging touch and motion data. Using machine learning models, particularly LSTM, the research demonstrates superior user classification accuracy compared to traditional RNN models, enhancing security against ATO attacks.

Курсовая работа по проектированию БД с GUI на PyQt6. Комплексная информационная система для управления каталогом мобильных устройств. Реализована нормализованная PostgreSQL база данных (3НФ), Python/PyQt6 интерфейс с полным CRUD-функционалом и система анализа производительности с 95% оптимизацией запросов.

On Windows, using a USB Wi-Fi Antenna and with Wi-Fi turned On we create a mobile hotspot and we communicate with our mobile devices using our created network.

Development of applications using the React Native framework on mobile operating systems: user interface, microservices and database for automation, testing and debugging purposes.