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Method and apparatus for measuring video quality using at least one semi-supervised learning regressor for mean observer score prediction

机译:使用至少一个半监督学习回归指标进行平均观看者分数预测来测量视频质量的方法和设备

摘要

The invention is made in the technical field of video quality measurement. More precisely, the invention is related to mean observer score prediction using a trained semi-supervised learning regressor. That is, a method and apparatus for measuring video quality using a semi-supervised learning system for mean observer score prediction is proposed. Said semi-supervised learning system comprises at least one semi-supervised learning regressor and said method comprises training the learning system and retraining the trained learning system using a selection of test data wherein the test data is used for determining at least one mean observer score prediction using the trained learning system and the selection is indicated by a feedback received through a user interface upon presenting, in the user interface, said at least one mean observer score prediction. Doing so, prediction quality can be improved after re-training at least for the selection.
机译:本发明是在视频质量测量技术领域中完成的。更精确地,本发明涉及使用训练有素的半监督学习回归器的平均观察者分数预测。即,提出了一种使用用于平均观察者分数预测的半监督学习系统来测量视频质量的方法和设备。所述半监督学习系统包括至少一个半监督学习回归器,并且所述方法包括使用选择的测试数据来训练学习系统和重新训练训练后的学习系统,其中所述测试数据用于确定至少一个平均观察者分数预测使用训练有素的学习系统,并且通过在用户界面中呈现所述至少一个平均观察者分数预测时通过用户界面接收的反馈来指示选择。这样做,至少在针对选择进行重新训练之后,可以提高预测质量。

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