[jira] [Created] (GUACAMOLE-1683) Implement super resolution machine learning model in Apache Guacamole client

["Trevor Sullivan (Jira)" <ji...@apache.org>]

Trevor Sullivan created GUACAMOLE-1683:
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             Summary: Implement super resolution machine learning model in Apache Guacamole client
                 Key: GUACAMOLE-1683
                 URL: https://issues.apache.org/jira/browse/GUACAMOLE-1683
             Project: Guacamole
          Issue Type: Wish
          Components: RDP, VNC
         Environment: Server: Linux virtual machine running on Linode
Client: Windows 11 with Google Chrome web browser
            Reporter: Trevor Sullivan


*Summary*

As an end user of Apache Guacamole, I would like improved screen resolution, especially for text content, without harming network performance. I am using Starlink satellite internet service, which has highly variable performance, sometimes fast, sometimes slow and unreliable. Using Apache Guacamole across a satellite internet connection yields varying results.

I cannot afford to increase screen resolution on the remote VNC Linux server, because that would severely damage performance, measured in frames per second (FPS).

*Implementation / Solution*

Implement a super resolution machine learning model into the Apache Guacamole VNC + RDP web clients. The super resolution model should apply in real-time, to the video stream coming from the remote server.

*Additional Notes*

I am willing to sacrifice some level of super resolution accuracy, in favor of improved screen resolution. Machine learning models can be trained to improve performance to approach closer to 100% accuracy, but will almost certainly never achieve 100% accuracy.

There is a research paper titled "{_}Implicit Transformer Network for Screen Content{_}
{_}Image Continuous Super-Resolution{_}" which covers this exact scenario, that was published in December 2021. Please see this document for details: [https://arxiv.org/pdf/2112.06174.pdf]

Tensorflow.js allegedly allows developers to implement machine learning models directly in the web browser. [https://www.tensorflow.org/js] 

 



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