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1,057–1,080 of 1,981 · Most stars

This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow

OneSignal makes engaging customers simple and is the fastest, most reliable service to send push notifications, in-app messages, SMS, and emails. This plugin makes it easy to integrate your React Native app with OneSignal. https://onesignal.com

  • react-native
  • onesignal
  • react-native-onesignal
  • push-notifications

Malleable C2 is a domain specific language to redefine indicators in Beacon's communication. This repository is a collection of Malleable C2 profiles that you may use. These profiles work with Cobalt Strike 3.x.

Winning Solution in NTIRE19 Challenges on Video Restoration and Enhancement (CVPR19 Workshops) - Video Restoration with Enhanced Deformable Convolutional Networks. EDVR has been merged into BasicSR and this repo is a mirror of BasicSR.

Q Light Controller Plus (QLC+) is a free and cross-platform software to control DMX or analog lighting systems like moving heads, dimmers, scanners etc. This project is a fork of the great QLC project written by Heikki Junnila that aims to continue the QLC development and to introduce new features.

  • c-plus-plus
  • qt
  • lighting
  • enttec

A complete, beginner-friendly bug bounty roadmap that takes you from zero experience to earning your first bounty.

Scripts and samples to support Confluent Demos, Talks, and Blogs. Not all of the examples in this repository are kept up to date. For automated tutorials and QA'd code, see https://github.com/confluentinc/tutorials/

💬 An extensive collection of exceptional resources dedicated to the captivating world of talking face synthesis! ⭐ If you find this repo useful, please give it a star! 🤩

  • arxiv
  • paper
  • audio-driven
  • synthesis

This custom component for Home Assistant will add crucial features to your climate-controlling TRV (Thermostatic Radiator Valves) to save you the work of creating automations to make it smart. It combines a room-temperature sensor, window/door sensors, weather forecasts, or an ambient temperature probe to decide when it should call for heat and automatically calibrate your TRVs to fix the imprecise measurements taken in the radiator's vicinity.