| Blind image quality assessment based on high order statistics aggregation J Xu, P Ye, Q Li, H Du, Y Liu, D Doermann IEEE Transactions on Image Processing 25 (9), 4444-4457, 2016 | 434 | 2016 |
| No-reference quality assessment for multiply-distorted images in gradient domain Q Li, W Lin, Y Fang IEEE Signal Processing Letters 23 (4), 541-545, 2016 | 230 | 2016 |
| Blind image quality assessment using statistical structural and luminance features Q Li, W Lin, J Xu, Y Fang IEEE Transactions on Multimedia 18 (12), 2457-2469, 2016 | 184 | 2016 |
| Objective quality assessment of screen content images by uncertainty weighting Y Fang, J Yan, J Liu, S Wang, Q Li, Z Guo IEEE Transactions on Image Processing 26 (4), 2016-2027, 2017 | 91 | 2017 |
| BSD: Blind image quality assessment based on structural degradation Q Li, W Lin, Y Fang Neurocomputing 236, 93-103, 2017 | 63 | 2017 |
| Multiple-level feature-based measure for retargeted image quality Y Zhang, W Lin, Q Li, W Cheng, X Zhang IEEE Transactions on image processing 27 (1), 451-463, 2017 | 53 | 2017 |
| A prediction backed model for quality assessment of screen content and 3-D synthesized images V Jakhetiya, K Gu, W Lin, Q Li, SP Jaiswal IEEE Transactions on Industrial Informatics 14 (2), 652-660, 2017 | 40 | 2017 |
| A highly efficient vehicle taillight detection approach based on deep learning Q Li, S Garg, J Nie, X Li, RW Liu, Z Cao, MS Hossain IEEE transactions on intelligent transportation systems 22 (7), 4716-4726, 2020 | 35 | 2020 |
| Perceptual evaluation of single-image super-resolution reconstruction G Wang, L Li, Q Li, K Gu, Z Lu, J Qian 2017 IEEE International Conference on Image Processing (ICIP), 3145-3149, 2017 | 29 | 2017 |
| Blind image quality assessment based on joint log-contrast statistics Q Li, W Lin, K Gu, Y Zhang, Y Fang Neurocomputing 331, 189-198, 2019 | 21 | 2019 |
| No-reference image quality assessment based on high order derivatives Q Li, W Lin, Y Fang 2016 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2016 | 21 | 2016 |
| Non-intrusive quality assessment for enhanced speech signals based on spectro-temporal features Q Li, Y Fang, W Lin, D Thalmann 2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), 1-6, 2014 | 20 | 2014 |
| Training-free referenceless camera image blur assessment via hypercomplex singular value decomposition L Tang, Q Li, L Li, K Gu, J Qian Multimedia Tools and Applications 77, 5637-5658, 2018 | 16 | 2018 |
| No-reference document image quality assessment based on high order image statistics J Xu, P Ye, Q Li, Y Liu, D Doermann 2016 IEEE International Conference on Image Processing (ICIP), 3289-3293, 2016 | 15 | 2016 |
| Bag-of-words representation for non-intrusive speech quality assessment Q Li, W Lin, Y Fang, D Thalmann 2015 IEEE China Summit and International Conference on Signal and …, 2015 | 11 | 2015 |
| Gradient-weighted structural similarity for image quality assessments Q Li, Y Fang, W Lin, D Thalmann 2015 IEEE International Symposium on Circuits and Systems (ISCAS), 2165-2168, 2015 | 11 | 2015 |
| A novel spatial pooling strategy for image quality assessment Q Li, YM Fang, JT Xu Journal of Computer Science and Technology 31 (2), 225-234, 2016 | 10 | 2016 |
| Local feature aggregation for blind image quality assessment J Xu, Q Li, P Ye, H Du, Y Liu 2015 Visual Communications and Image Processing (VCIP), 1-4, 2015 | 6 | 2015 |
| Objective quality assessment of screen content images by structure information Y Fang, J Yan, J Liu, S Wang, Q Li, Z Guo Advances in Multimedia Information Processing-PCM 2016: 17th Pacific-Rim …, 2016 | 4 | 2016 |
| No-reference image quality assessment based on structural and luminance information Q Li, W Lin, J Xu, Y Fang, D Thalmann MultiMedia Modeling: 22nd International Conference, MMM 2016, Miami, FL, USA …, 2016 | 3 | 2016 |
Yuming FangJiangxi University of Finance and EconomicsVerified email at ntu.edu.sg
