@inproceedings{
 title = {Objective Video Quality Assessment Based on Neural Networks},
 type = {inproceedings},
 year = {2016},
 keywords = {Video quality assessment,neural networks,quality of experience},
 volume = {96},
 id = {9cfefe46-717c-3156-8508-fca8f32cfbb1},
 created = {2019-02-14T18:02:01.196Z},
 file_attached = {false},
 profile_id = {74e7d4ea-3dac-3118-aab9-511a5b337e8f},
 last_modified = {2019-02-14T18:02:01.196Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© 2016 The Authors. Published by Elsevier B.V. Image/Video Quality Assessment (IQA/VQA) plays a significant role in image and video processing, as it can directly predict the impact of distortions on the video in the quality of experience (QoE) of the user. For this propose, in this paper, it is presented a new method for objective video quality assessment using an artificial neural network to predict the subjective evaluation of the video as if it were observed by a human user. The network was trained using degradation indicators extracted from the VQEG Phase I video database, which describe the level of distortion suffered by the original video under spatial and temporal scopes. The proposed method obtained an excellent correlation with the subjective scores over this same database.},
 bibtype = {inproceedings},
 author = {Menor, D.P.A. and Mello, C.A.B. and Zanchettin, C.},
 doi = {10.1016/j.procs.2016.08.202},
 booktitle = {Procedia Computer Science}
}

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