Based on random neural networks, a cross-layer prediction model is proposed for estimating the perceptual quality of mobile video in no reference mode.

Based on random neural networks, a cross-layer prediction model is proposed for estimating the perceptual quality of mobile video in no reference mode.

Based on random neural networks, a cross-layer prediction model is proposed for estimating the perceptual quality of mobile video in no reference mode.

Duration: 2:22
Posted: Feb 23, 2016

Based on random neural networks, a cross-layer prediction model is proposed for estimating the perceptual quality of mobile video in no reference mode. The ...

Therefore, in wireless sensor networks, video devices need not only to assure the QoE for video applications, but also to deal with the huge energy consumption ...

For this purpose, Random. Forest is applied to predict three objective QoE metrics, i.e., rebuffering fre- quency, mean bitrate and bitrate switch frequency, ...

For example, the prediction of. QoE for video can be performed by applying mathematical models based on QoS parameters [2]–[4], signal processing techniques [5] ...

We present the prediction of customer satisfaction relative to network coverage and video streaming using robust machine learning models like Neural Networks.

The tool is based on statistic learning using random neural network which is trained to learn mapping between QoE scores and technical parameters. It has to be ...