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https://google.github.io/gsocguides/student/proposal-example-1
https://google.github.io/gsocguides/student/proposal-example-2

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Active projects for 2019

Info

GENIVI has applied for a GSoC slot again this year! Pending acceptance.

Now is the time to consider project proposals and to volunteer for mentorship.

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(green star) ACTIVE Voice control research

During 2018 a successful research-oriented project was completed which showed smart interaction through combining machine-learning neural network decisions with basic algorithmic approaches.  The project combined the best of two worlds to achieve surprisingly good results using simple means. The end result was natural-language interaction to play media files from a diverse set, and to navigate to a point of interest.

In this project you will extend the work, trying new methods, integrating more existing libraries (for speech input and output), modifying the machine-learning networks and traditional algorithmic approaches to enable new innovative voice interaction.

A successful application should present their own ideas around what features to achieve and technologies to use.

Requirements: Some experience of programming in Python and C/C++ on Linux is required and some machine learning experience - preferably with TensorFlow.
Experience of Yocto and embedded systems is a plus.

Potential Mentors: To be announced.

(green star) ACTIVE Graphics distribution with RAMSES

Recently a significant graphics distribution framework was released as open-source code under GENIVI's umbrella, to foster continued development.  This state-of-the-art 3D graphics framework enables very efficient distribution of graphics across multiple systems using the transfer of Scene Graph information instead of ready-rendered graphical bitmaps.

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Mentors: RAMSES developers from BMW.

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Other proposed projects for 2019

Info

GENIVI has applied for a GSoC slot again this year! Pending acceptance.

Now is the time to consider project proposals and to volunteer for mentorship.

(blue star)  Next-generation message communication in heterogeneous systems,
including AUTOSAR-based systems and cloud data

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Potential Mentors: To be announced.

Voice control research

During 2018 a successful research-oriented project was completed which showed smart interaction through combining machine-learning neural network decisions with basic algorithmic approaches.  The project combined the best of two worlds to achieve surprisingly good results using simple means. The end result was natural-language interaction to play media files from a diverse set, and to navigate to a point of interest.

In this project you will extend the work, trying new methods, integrating more existing libraries (for speech input and output), modifying the machine-learning networks and traditional algorithmic approaches to enable new innovative voice interaction.

A successful application should present their own ideas around what features to achieve and technologies to use.

Requirements: Some experience of programming in Python and C/C++ on Linux is required and some machine learning experience - preferably with TensorFlow.
Experience of Yocto and embedded systems is a plus.

Potential Mentors: To be announced.

Debian / Ubuntu packaging for GENIVI subsystems

Many companies use Ubuntu or other popular  as a software development tool in automotive, even if the target system is not Ubuntu.  Some systems go further and build embedded/automotive systems on the Debian tools and technologies.  Fundamental components such as DLT are popular and often a prerequisite for other GENIVI components.   Packaging work work is fairly straight forward and there is even a bug in Debian for this: https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=688586;msg=5 

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