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Found 6 papers, 0 papers with code
Deep Learning-Based Real-Time Quality Control of Standard Video Compression for Live Streaming
The encoded bitrate and the quality of the compressed video depend on encoder parameters, specifically, the quantization parameter (QP).
Deep Learning-Based Real-Time Rate Control for Live Streaming on Wireless Networks
The objective is to maintain an encoded video bitrate slightly below the available channel bitrate.
Semantic Multi-Resolution Communications
The experiment with both datasets illustrates that our proposed method is capable of surpassing the SSCC method in reconstructing data with different resolutions, enabling the extraction of semantic features with heightened confidence in successive layers.
Elixir: A system to enhance data quality for multiple analytics on a video stream
Elixir correctly detects 7. 1% (22, 068) and 5. 0% (15, 731) more cars, 94% (551) and 72% (478) more faces, and 670. 4% (4975) and 158. 6% (3507) more persons than the default-setting and time-sharing approaches, respectively.
Enhancing Video Analytics Accuracy via Real-time Automated Camera Parameter Tuning
We then present CamTuner, to our knowledge, the first framework that dynamically adapts NAUTO camera parameters to optimize the accuracy of AUs in a VAP in response to adverse changes in environmental conditions.
AQuA: Analytical Quality Assessment for Optimizing Video Analytics Systems
Millions of cameras at edge are being deployed to power a variety of different deep learning applications.
