Contributions
[ Source: InfoVista SAS (France) ]  |
|
Numéro
|
Titre
|
Source
|
AI/Question
|
Date
|
|
[ 564 ]
|
Infovista proposal for P.VSQMTF.1 and P.565
|
InfoVista SAS (France)
|
Q15/12
|
2021-09-03 |
|
[ 540 ]
|
Findings from P.VSQMTF.1 independent validation
|
InfoVista SAS (France)
|
Q15/12
|
2021-04-21 |
|
[ 539 ]
|
An approach for generic testing techniques on real application data traffic patterns within the context of G.IntAct
|
InfoVista SAS (France)
|
Q17/12
|
2021-04-21 |
|
[ 475 ]
|
A Predictor of Speech Quality by Machine Learning based on P.565 framework
|
InfoVista SAS (France)
|
Q15/12
|
2020-04-01 |
|
[ 413 ]
(Rev.1) |
Proposed additions and corrections for ITU-T Rec. P.1401
|
Ilmenau University of Technology (TU Ilmenau) (Germany)
,
InfoVista SAS (France)
,
Rohde & Schwarz GmbH & Co. KG (Germany)
,
Telefon AB - LM Ericsson (Sweden)
|
Q9/12
|
2019-11-12 |
|
[ 411 ]
|
Proposed Generic Client for Voice OTT Services
|
InfoVista SAS (France)
|
Q17/12
|
2019-11-11 |
|
[ 410 ]
(Rev.1) |
Proposed Guidelines for Machine Learning Based Solutions
|
InfoVista SAS (France)
|
Q9/12, Q15/12, Q14/12
|
2019-11-11 |
|
[ 385 ]
(Rev.1) |
Methods, metrics and procedures for statistical evaluation, qualification and comparison of objective quality prediction models
|
InfoVista SAS (France)
,
Rohde & Schwarz GmbH & Co. KG (Germany)
|
Q9/12
|
2019-04-24 |
|
[ 377 ]
|
Minimum Performance Requirements for Machine Learning Based Solutions
|
InfoVista SAS (France)
|
Q9/12, Q15/12
|
2019-04-24 |
|
[ 313 ]
(Rev.1) |
A Machine Learning Approach in SG12
|
InfoVista SAS (France)
|
Q16/12, Q15/12, Q1/12
|
2018-11-14 |
|
[ 256 ]
|
Draft Text for a New Recommendation "Voice Service Quality Monitoring and Troubleshooting Framework for Intrusive Parametric Voice QoE Prediction, P.VSQMTF"
|
InfoVista SAS (France)
|
Q15/12
|
2018-11-12 |
|
[ 255 ]
|
P.VSQMTF Differences vis a vis P.564
|
InfoVista SAS (France)
|
Q15/12
|
2018-11-12 |
Resultats:12 documents
|
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