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Evaluating Users' Satisfaction in Packet Networks Using Random Neural Networks
- Source :
- Artificial Neural Networks-ICANN 2006, International Conference on Artifical Neural Networks, International Conference on Artifical Neural Networks, Sep 2006, Athens, Greece. pp.303-312, ⟨10.1007/11840817_32⟩, Artificial Neural Networks – ICANN 2006 ISBN: 9783540386254, ICANN (1)
- Publication Year :
- 2006
- Publisher :
- HAL CCSD, 2006.
-
Abstract
- International audience; Quantifying the quality of a video or audio transmission over the Internet is usually a hard task, as based on the statistical processing of the evaluations made by a panel of humans (the corresponding and standardized area is called subjective testing). In this paper we describe a methodology called Pseudo-Subjective Quality Assessment (PSQA), based on Random Neural Networks, which is able to perform this task automatically, accurately and efficiently. RNN had been chosen here because of their good performances over other possibilities; this is discussed in the paper. Some new insights on PSQA's use and performance are also given. In particular we discuss new results concerning PSQA-based dynamic quality control, and conversational quality assessment.
- Subjects :
- Computer science
Image quality
media_common.quotation_subject
02 engineering and technology
[INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]
Machine learning
computer.software_genre
Task (project management)
[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]
Packet switching
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]
0202 electrical engineering, electronic engineering, information engineering
Random neural networks
Quality (business)
Multimedia quality assesment
media_common
Artificial neural network
Artificial neural networks
business.industry
Network packet
020206 networking & telecommunications
PSQA
Transmission (telecommunications)
020201 artificial intelligence & image processing
The Internet
Artificial intelligence
business
computer
Subjects
Details
- Language :
- English
- ISBN :
- 978-3-540-38625-4
- ISBNs :
- 9783540386254
- Database :
- OpenAIRE
- Journal :
- Artificial Neural Networks-ICANN 2006, International Conference on Artifical Neural Networks, International Conference on Artifical Neural Networks, Sep 2006, Athens, Greece. pp.303-312, ⟨10.1007/11840817_32⟩, Artificial Neural Networks – ICANN 2006 ISBN: 9783540386254, ICANN (1)
- Accession number :
- edsair.doi.dedup.....ab087d097eb5cb07fd0935c506e72628
- Full Text :
- https://doi.org/10.1007/11840817_32⟩