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Showing 6 open source projects for "screen"
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SalesTarget.ai | AI-Powered Lead Generation, Email Outreach, and CRMSalesTarget is ideal for B2B sales teams, startup founders, and marketing professionals looking to streamline lead generation and outreach. It also benefits growing SaaS companies and agencies aiming to scale their outbound efforts efficiently.
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MagicMirror²
Modular smart mirror platform with a list of installable modules
MagicMirror² is Open Source, free and maintained by a big group of enthusiasts. Got a nice idea? Send us a pull request and become a part of the big list of contributors. The core of MagicMirror² contains a strong API which allows 3rd party developers to build additional modules. Modules you can use. Modules you can develop. Read our extensive documentation to find out everything you want to know about the MagicMirror² project. The full API description allows you to build your own modules.... -
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ViZDoom
Doom-based AI research platform for reinforcement learning
ViZDoom allows developing AI bots that play Doom using only the visual information (the screen buffer). It is primarily intended for research in machine visual learning, and deep reinforcement learning, in particular. ViZDoom is based on ZDOOM, the most popular modern source-port of DOOM. This means compatibility with a huge range of tools and resources that can be used to create custom scenarios, availability of detailed documentation of the engine and tools and support of Doom community. ... -
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PandaOCR
Multifunctional OCR Image and Text Recognition
...You can continue to use the regular version for free as before, without worrying about deactivating the regular version after the launch of the professional version. If you have higher needs, you can try the professional version. You can also use the Baidu API interface without activation. Support shortcut keys and screen corner trigger screenshot recognition function, convenient and fast. -
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BerryNet
Deep learning gateway on Raspberry Pi and other edge devices
This project turns edge devices such as Raspberry Pi into an intelligent gateway with deep learning running on it. No internet connection is required, everything is done locally on the edge device itself. Further, multiple edge devices can create a distributed AIoT network. At DT42, we believe that bringing deep learning to edge devices is the trend towards the future. It not only saves costs of data transmission and storage but also makes devices able to respond according to the events... -
Peer to Peer Recognition Brings Teams TogetherCreate a positive and energetic workplace environment with Motivosity, an innovative employee recognition and engagement platform. With Motivosity, employees can give each other small monetary bonuses for doing great things, promoting trust, collaboration, and appreciation in the workplace. The software solution comes with features such as an open-currency open-reward system, insights and analytics, dynamic organization chart, award programs, milestones, and more.
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Docker Machine
Machine management for a container-centric world
...Point the Machine CLI at a running, managed host, and you can run docker commands directly on that host. For example, run docker-machine env default to point to a host called default, follow on-screen instructions to complete env setup, and run docker ps, docker run hello-world, and so forth. Machine was the only way to run Docker on Mac or Windows previous to Docker v1.12. -
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nn22 Basic Neural Networks for Octave
Simple .m files, Basic Neural Networks study for Octave (or Matlab)
...The code is completely open to be modified and may suit several scenarios. The code commenting is verbose, and variables and functions do respect English formatting, so that code may be self explanatory. Messages to the screen are localized, both in English and Spanish, and it is really easy to add another language to the localization. If any further explanation is needed, the forum/discussion page may be of help :) Comments and suggestions are very welcome.
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