@inproceedings{d0376584cf044d0d991d1dcbdd3e75a6,
title = "Simultaneous estimation of image quality and distortion via multi-task convolutional neural networks",
abstract = "In this work we describe a compact multi-task Convolutional Neural Network (CNN) for simultaneously estimating image quality and identifying distortions. CNNs are natural choices for multi-task problems because learned convolutional features may be shared by different high level tasks. However, we empirically argue that simply appending additional tasks based on the state of the art structure (e.g., [1]) does not lead to optimal solutions. We design a compact structure with nearly 90\% fewer parameters compared to [1], and demonstrate its learning power.",
keywords = "CNN, image distortion classification, Image quality assessment, no-reference",
author = "Le Kang and Peng Ye and Yi Li and David Doermann",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Conference on Image Processing, ICIP 2015 ; Conference date: 27-09-2015 Through 30-09-2015",
year = "2015",
month = dec,
day = "9",
doi = "10.1109/ICIP.2015.7351311",
language = "English",
series = "Proceedings - International Conference on Image Processing, ICIP",
publisher = "IEEE Computer Society",
pages = "2791--2795",
booktitle = "2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings",
address = "United States",
}