Stereoscopic Image Quality Assessment Based on Deep Convolutional Neural Models
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[1] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[2] Yang Zhao,et al. Blind assessment for stereo images considering binocular characteristics and deep perception map based on deep belief network , 2019, Inf. Sci..
[3] Yoshua Bengio,et al. Maxout Networks , 2013, ICML.
[4] Andrey S. Krylov,et al. 3D No-Reference Image Quality Assessment via Transfer Learning and Saliency-Guided Feature Consolidation , 2019, IEEE Access.
[5] Sumohana S. Channappayya,et al. Generating Image Distortion Maps Using Convolutional Autoencoders With Application to No Reference Image Quality Assessment , 2019, IEEE Signal Processing Letters.
[6] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[7] Wei Zhou,et al. Dual-Stream Interactive Networks for No-Reference Stereoscopic Image Quality Assessment , 2019, IEEE Transactions on Image Processing.
[8] Yann LeCun,et al. Learning a similarity metric discriminatively, with application to face verification , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[9] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[10] Trevor Darrell,et al. Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.
[11] Yoram Singer,et al. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization , 2011, J. Mach. Learn. Res..
[12] Sanghoon Lee,et al. Fully Deep Blind Image Quality Predictor , 2017, IEEE Journal of Selected Topics in Signal Processing.
[13] Geoffrey E. Hinton,et al. On the importance of initialization and momentum in deep learning , 2013, ICML.
[14] Joost van de Weijer,et al. RankIQA: Learning from Rankings for No-Reference Image Quality Assessment , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[15] Andrey S. Krylov,et al. No-Reference Stereoscopic Image Quality Assessment Using Convolutional Neural Network for Adaptive Feature Extraction , 2018, IEEE Access.
[16] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[17] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[18] Feng Shao,et al. 3D Visual Attention for Stereoscopic Image Quality Assessment , 2014, J. Softw..
[19] Jiro Katto,et al. A Pre-Saliency Map Based Blind Image Quality Assessment via Convolutional Neural Networks , 2017, 2017 IEEE International Symposium on Multimedia (ISM).
[20] Paolo Napoletano,et al. On the use of deep learning for blind image quality assessment , 2016, Signal Image Video Process..
[21] Ling-Yu Duan,et al. Finding the Secret of Image Saliency in the Frequency Domain , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[22] Fei Gao,et al. DeepSim: Deep similarity for image quality assessment , 2017, Neurocomputing.
[23] Do-Kyoung Kwon,et al. Full-reference quality assessment of stereopairs accounting for rivalry , 2013, Signal Process. Image Commun..
[24] Nathan Srebro,et al. The Marginal Value of Adaptive Gradient Methods in Machine Learning , 2017, NIPS.
[25] Tom Schaul,et al. Unit Tests for Stochastic Optimization , 2013, ICLR.
[26] Lei Zhang,et al. Waterloo Exploration Database: New Challenges for Image Quality Assessment Models , 2017, IEEE Transactions on Image Processing.
[27] Geoffrey E. Hinton,et al. Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.
[28] Nikolay N. Ponomarenko,et al. Image database TID2013: Peculiarities, results and perspectives , 2015, Signal Process. Image Commun..
[29] Ning Qian,et al. On the momentum term in gradient descent learning algorithms , 1999, Neural Networks.
[30] Alan C. Bovik,et al. Subjective evaluation of stereoscopic image quality , 2013, Signal Process. Image Commun..
[31] Alan C. Bovik,et al. No-Reference Image Quality Assessment in the Spatial Domain , 2012, IEEE Transactions on Image Processing.
[32] Qiang Yang,et al. A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.
[33] Lai-Man Po,et al. No-reference image quality assessment with deep convolutional neural networks , 2016, 2016 IEEE International Conference on Digital Signal Processing (DSP).
[34] Weilong Hou,et al. Saliency-Guided Deep Framework for Image Quality Assessment , 2015 .
[35] Yi Li,et al. Convolutional Neural Networks for No-Reference Image Quality Assessment , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[36] Nitish Srivastava,et al. Improving neural networks by preventing co-adaptation of feature detectors , 2012, ArXiv.
[37] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[38] Mei Yu,et al. No-reference Stereoscopic Image Quality Assessment Using Binocular Self-similarity and Deep Neural Network , 2016, Signal Process. Image Commun..
[39] Andrey S. Krylov,et al. Learning Local Quality-Aware Structures of Salient Regions for Stereoscopic Images via Deep Neural Networks , 2020, IEEE Transactions on Multimedia.
[40] Andrey S. Krylov,et al. Stereoscopic Image Quality Assessment by Considering Binocular Visual Mechanisms , 2018, IEEE Access.
[41] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[42] Sepp Hochreiter,et al. Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) , 2015, ICLR.
[43] Trevor Darrell,et al. Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[44] Lin Ma,et al. Learning structure of stereoscopic image for no-reference quality assessment with convolutional neural network , 2016, Pattern Recognit..
[45] Jiwen Lu,et al. PCANet: A Simple Deep Learning Baseline for Image Classification? , 2014, IEEE Transactions on Image Processing.
[46] Alan C. Bovik,et al. A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms , 2006, IEEE Transactions on Image Processing.
[47] Yoshua Bengio,et al. Deep Learning of Representations for Unsupervised and Transfer Learning , 2011, ICML Unsupervised and Transfer Learning.
[48] Ioannis A. Kakadiaris,et al. End-to-End 3D Face Reconstruction with Deep Neural Networks , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[49] Sanghoon Lee,et al. Blind Deep S3D Image Quality Evaluation via Local to Global Feature Aggregation , 2017, IEEE Transactions on Image Processing.
[50] David S. Doermann,et al. Unsupervised feature learning framework for no-reference image quality assessment , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[51] Xuelong Li,et al. Blind Image Quality Assessment via Deep Learning , 2015, IEEE Transactions on Neural Networks and Learning Systems.
[52] Lin Ma,et al. Multimodal learning for facial expression recognition , 2015, Pattern Recognit..