Stereoscopic image quality assessment via convolutional neural networks

2017 International Smart Cities Conference (ISC2) ◽

10.1109/isc2.2017.8090873 ◽

2017 ◽

Author(s):

Qingbing Sang ◽

Tingting Gu ◽

Chaofeng Li ◽

Xiaojun Wu

Keyword(s):

Neural Networks ◽

Image Quality ◽

Quality Assessment ◽

Convolutional Neural Networks ◽

Image Quality Assessment ◽

Stereoscopic Image

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Blind Stereoscopic Image Quality Assessment Using Convolutional Neural Networks and Support Vector Regression

2018 9th International Symposium on Signal, Image, Video and Communications (ISIVC) ◽

10.1109/isivc.2018.8709203 ◽

2018 ◽

Author(s):

Aladine Chetouani ◽

Mohammed El Hassouni ◽

Rachid Jennane

Keyword(s):

Neural Networks ◽

Image Quality ◽

Quality Assessment ◽

Support Vector Regression ◽

Convolutional Neural Networks ◽

Image Quality Assessment ◽

Support Vector ◽

Stereoscopic Image

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A Data-Driven No-Reference Image Quality Assessment via Deep Convolutional Neural Networks

Advances in Multimedia Information Processing – PCM 2018 - Lecture Notes in Computer Science ◽

10.1007/978-3-030-00767-6_34 ◽

2018 ◽

pp. 361-371

Author(s):

Yezhao Fan ◽

Yuchen Zhu ◽

Guangtao Zhai ◽

Jia Wang ◽

Jing Liu

Keyword(s):

Neural Networks ◽

Image Quality ◽

Quality Assessment ◽

Convolutional Neural Networks ◽

Image Quality Assessment ◽

Data Driven ◽

Reference Image ◽

Deep Convolutional Neural Networks

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No-reference image quality assessment with deep convolutional neural networks

2016 IEEE International Conference on Digital Signal Processing (DSP) ◽

10.1109/icdsp.2016.7868646 ◽

2016 ◽

Author(s):

Yuming Li ◽

Lai-Man Po ◽

Litong Feng ◽

Fang Yuan

Keyword(s):

Neural Networks ◽

Image Quality ◽

Quality Assessment ◽

Convolutional Neural Networks ◽

Image Quality Assessment ◽

Reference Image ◽

Deep Convolutional Neural Networks

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No-Reference Image Quality Assessment Based on Multi-scale Convolutional Neural Networks

Advances in Intelligent Systems and Computing - Intelligent Computing ◽

10.1007/978-3-030-22868-2_84 ◽

2019 ◽

pp. 1202-1216

Author(s):

Peikun Chen ◽

Yuzhen Niu ◽

Dong Huang

Keyword(s):

Neural Networks ◽

Image Quality ◽

Quality Assessment ◽

Convolutional Neural Networks ◽

Image Quality Assessment ◽

Reference Image ◽

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Context-dependent image quality assessment of JPEG compressed Mars Science Laboratory Mastcam images using convolutional neural networks

Computers & Geosciences ◽

10.1016/j.cageo.2018.06.001 ◽

2018 ◽

Vol 118 ◽

pp. 109-121 ◽

Author(s):

Hannah R. Kerner ◽

James F. Bell ◽

Heni Ben Amor

Keyword(s):

Neural Networks ◽

Image Quality ◽

Quality Assessment ◽

Convolutional Neural Networks ◽

Image Quality Assessment ◽

Science Laboratory ◽

Mars Science Laboratory ◽

Context Dependent

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No-reference image quality assessment using Prewitt magnitude based on convolutional neural networks

Signal Image and Video Processing ◽

10.1007/s11760-015-0784-2 ◽

2015 ◽

Vol 10 (4) ◽

pp. 609-616 ◽

Author(s):

Jie Li ◽

Lian Zou ◽

Jia Yan ◽

Dexiang Deng ◽

Tao Qu ◽

...

Keyword(s):

Neural Networks ◽

Image Quality ◽

Quality Assessment ◽

Convolutional Neural Networks ◽

Image Quality Assessment ◽

Reference Image

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Face image quality assessment for face selection in surveillance video using convolutional neural networks

2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP) ◽

10.1109/globalsip.2015.7418261 ◽

2015 ◽

Author(s):

S. Vignesh ◽

K.V.S.N.L. Manasa Priya ◽

Sumohana S. Channappayya

Keyword(s):

Neural Networks ◽

Image Quality ◽

Quality Assessment ◽

Convolutional Neural Networks ◽

Image Quality Assessment ◽

Surveillance Video

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A Pre-Saliency Map Based Blind Image Quality Assessment via Convolutional Neural Networks

2017 IEEE International Symposium on Multimedia (ISM) ◽

10.1109/ism.2017.21 ◽

2017 ◽

Author(s):

Zhengxue Cheng ◽

Masaru Takeuchi ◽

Jiro Katto

Keyword(s):

Neural Networks ◽

Image Quality ◽

Quality Assessment ◽

Convolutional Neural Networks ◽

Image Quality Assessment ◽

Saliency Map ◽

Blind Image Quality Assessment ◽

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Convolutional Neural Networks for No-Reference Image Quality Assessment

2014 IEEE Conference on Computer Vision and Pattern Recognition ◽

10.1109/cvpr.2014.224 ◽

2014 ◽

Author(s):

Le Kang ◽

Peng Ye ◽

Yi Li ◽

David Doermann

Keyword(s):

Neural Networks ◽

Image Quality ◽

Quality Assessment ◽

Convolutional Neural Networks ◽

Image Quality Assessment ◽

Reference Image

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No Reference Image Quality Assessment based on Multi-Expert Convolutional Neural Networks

IEEE Access ◽

10.1109/access.2018.2802498 ◽

2018 ◽

Vol 6 ◽

pp. 8934-8943 ◽

Author(s):

Chunling Fan ◽

Yun Zhang ◽

Liangbing Feng ◽

Qingshan Jiang

Keyword(s):

Neural Networks ◽

Image Quality ◽

Quality Assessment ◽

Convolutional Neural Networks ◽

Image Quality Assessment ◽

Reference Image

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