Name
Abstract | ||
|---|---|---|
The ever-increasing demand for seamless high-definition video streaming, along with the widespread adoption of the dynamic adaptive streaming over HTTP (DASH) standard, has been a major driver of the large amount of research on bitrate adaptation algorithms. The complexity and variability of the video content and of the mobile wireless channel make this an ideal application for learning approaches... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TCCN.2017.2755007 | IEEE Transactions on Cognitive Communications and Networking |
Keywords | Field | DocType |
Streaming media,Heuristic algorithms,Bit rate,Neural networks,Dynamic programming | Heuristic,Computer science,Q-learning,Real-time computing,Dynamic Adaptive Streaming over HTTP,Quality of experience,Artificial intelligence,Deep learning,Artificial neural network,Dash,Reinforcement learning | Journal |
Volume | Issue | ISSN |
3 | 4 | 2332-7731 |
Citations | PageRank | References |
17 | 0.85 | 33 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matteo Gadaleta | 1 | 28 | 1.72 |
| Federico Chiariotti | 2 | 88 | 12.75 |
| Michele Rossi | 3 | 228 | 26.33 |
| Andrea Zanella | 4 | 1920 | 131.55 |