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WANG JIHENG
WANG JIHENG
Apple Inc.
Подтвержден адрес электронной почты в домене apple.com - Главная страница
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Процитировано
Год
Quality prediction of asymmetrically distorted stereoscopic 3D images
J Wang, A Rehman, K Zeng, S Wang, Z Wang
IEEE Transactions on Image Processing 24 (11), 3400-3414, 2015
1582015
Perceptual quality assessment of high frame rate video
RM Nasiri, J Wang, A Rehman, S Wang, Z Wang
2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP …, 2015
492015
Stereoscopic image quality assessment by deep convolutional neural network
Y Fang, J Yan, X Liu, J Wang
Journal of Visual Communication and Image Representation 58, 400-406, 2019
452019
Asymmetrically compressed stereoscopic 3D videos: Quality assessment and rate-distortion performance evaluation
J Wang, S Wang, Z Wang
IEEE Transactions on Image Processing 26 (3), 1330-1343, 2017
452017
Quality prediction of asymmetrically distorted stereoscopic images from single views
J Wang, K Zeng, Z Wang
IEEE International Conference on Multimedia and Expo, 2014
432014
SSIM-motivated two-pass VBR coding for HEVC
S Wang, A Rehman, K Zeng, J Wang, Z Wang
IEEE Transactions on Circuits and Systems for Video Technology 27 (10), 2189 …, 2016
412016
Comparison of dual energy subtraction chest radiography and traditional chest X-rays in the detection of pulmonary nodules
F Manji, J Wang, G Norman, Z Wang, D Koff
Quantitative imaging in medicine and surgery 6 (1), 1, 2016
402016
The quest for'diagnostically lossless' medical image compression: a comparative study of objective quality metrics for compressed medical images
I Kowalik-Urbaniak, D Brunet, J Wang, D Koff, N Smolarski-Koff, ...
Medical imaging 2014: image perception, observer performance, and technology …, 2014
402014
Image classification based on complex wavelet structural similarity
A Rehman, Y Gao, J Wang, Z Wang
Signal Processing: Image Communication 28 (8), 984-992, 2013
372013
Perceptual quality of asymmetrically distorted stereoscopic images: the role of image distortion types
J Wang, Z Wang
International Workshop on Video Processing and Quality Metrics for Consumer …, 2014
332014
Perceptual depth quality in distorted stereoscopic images
J Wang, S Wang, K Ma, Z Wang
IEEE Transactions on Image Processing 26 (3), 1202-1215, 2016
312016
SSIM-based coarse-grain scalable video coding
T Zhao, J Wang, Z Wang, CW Chen
IEEE Transactions on Broadcasting 61 (2), 210-221, 2015
302015
From H. 264 to HEVC: coding gain predicted by objective video quality assessment models
K Zeng, A Rehman, J Wang, Z Wang
2013 International Workshop on Video Processing and Quality Metrics for …, 2013
242013
Functional data classification for temporal gene expression data with kernel-induced random forests
G Fan, J Cao, J Wang
2010 IEEE Symposium on Computational Intelligence in Bioinformatics and …, 2010
192010
Learning a no-reference quality predictor of stereoscopic images by visual binocular properties
Y Fang, J Yan, J Wang, X Liu, G Zhai, P Le Callet
IEEE Access 7, 132649-132661, 2019
172019
Perceptual quality assessment for asymmetrically distorted stereoscopic video by temporal binocular rivalry
Y Fang, X Sui, J Wang, J Yan, J Lei, P Le Callet
IEEE Transactions on Circuits and Systems for Video Technology 31 (8), 3010-3024, 2020
142020
Cw-ssim kernel based random forest for image classification
G Fan, Z Wang, J Wang
Visual Communications and Image Processing 2010 7744, 686-693, 2010
142010
Quality prediction of asymmetrically compressed stereoscopic videos
J Wang, S Wang, Z Wang
2015 IEEE International Conference on Image Processing (ICIP), 3427-3431, 2015
132015
Modelling of subjective radiological assessments with objective image quality measures of brain and body CT images
IA Kowalik-Urbaniak, J Castelli, N Hemmati, D Koff, N Smolarski-Koff, ...
Image Analysis and Recognition: 12th International Conference, ICIAR 2015 …, 2015
132015
No reference quality assessment for stereoscopic images by statistical features
Y Fang, J Yan, J Wang
2017 Ninth International Conference on Quality of Multimedia Experience …, 2017
92017
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