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Books and Theses
- 2020
[b1]Pak Lun Kevin Ding:
Super-resolution for Natural Images and Magnetic Resonance Images. Arizona State University, Tempe, USA, 2020
Journal Articles
- 2022
- [j7]Kan Chang
, Hengxin Li, Yufei Tan, Pak Lun Kevin Ding, Baoxin Li:
A Two-Stage Convolutional Neural Network for Joint Demosaicking and Super-Resolution. IEEE Trans. Circuits Syst. Video Technol. 32(7): 4238-4254 (2022) - 2020
- [j6]Kan Chang, Minghong Li, Pak Lun Kevin Ding, Baoxin Li:
Accurate single image super-resolution using multi-path wide-activated residual network. Signal Process. 172: 107567 (2020) - 2019
- [j5]Kan Chang, Xueyu Zhang, Pak Lun Kevin Ding, Baoxin Li:
Data-adaptive low-rank modeling and external gradient prior for single image super-resolution. Signal Process. 161: 36-49 (2019) - 2018
- [j4]Kan Chang, Pak Lun Kevin Ding, Baoxin Li:
Single image super-resolution using collaborative representation and non-local self-similarity. Signal Process. 149: 49-61 (2018) - [j3]Kan Chang, Pak Lun Kevin Ding, Baoxin Li:
Single Image Super Resolution Using Joint Regularization. IEEE Signal Process. Lett. 25(4): 596-600 (2018) - 2016
- [j2]Kan Chang, Pak Lun Kevin Ding, Baoxin Li:
Compressive Sensing Reconstruction of Correlated Images Using Joint Regularization. IEEE Signal Process. Lett. 23(4): 449-453 (2016) - 2015
- [j1]Kan Chang, Pak Lun Kevin Ding, Baoxin Li:
Color image demosaicking using inter-channel correlation and nonlocal self-similarity. Signal Process. Image Commun. 39: 264-279 (2015)
Conference and Workshop Papers
- 2024
- [c7]Riti Paul, Sahil Vora, Pak Lun Kevin Ding, Ameet Patel, Leland Hu, Baoxin Li, Yuxiang Zhou:
Transferable Variational Feedback Network for Vendor Generalization in Accelerated MRI. AIiH (2) 2024: 48-63 - 2020
- [c6]Pak Lun Kevin Ding, Sarah Martin, Baoxin Li:
Improving Batch Normalization with Skewness Reduction for Deep Neural Networks. ICPR 2020: 7165-7172 - 2019
- [c5]Pak Lun Kevin Ding, Zhiqiang Li, Yuxiang Zhou, Baoxin Li:
Deep residual dense U-Net for resolution enhancement in accelerated MRI acquisition. Medical Imaging: Image Processing 2019: 109490F - [c4]Xu Zhou, Pak Lun Kevin Ding, Baoxin Li:
Improving Robustness of Random Forest Under Label Noise. WACV 2019: 950-958 - 2017
- [c3]Parag S. Chandakkar, Yikang Li, Pak Lun Kevin Ding, Baoxin Li:
Strategies for Re-Training a Pruned Neural Network in an Edge Computing Paradigm. EDGE 2017: 244-247 - [c2]Pak Lun Kevin Ding, Baoxin Li, Kan Chang:
Convex dictionary learning for single image super-resolution. ICIP 2017: 4058-4062 - [c1]Xu Zhou, Pak Lun Kevin Ding, Baoxin Li:
Non-negative dictionary learning with pairwise partial similarity constraint. ICME 2017: 1410-1415
Informal and Other Publications
- 2020
- [i3]Pak Lun Kevin Ding, Zhiqiang Li, Yuxiang Zhou, Baoxin Li:
Deep Residual Dense U-Net for Resolution Enhancement in Accelerated MRI Acquisition. CoRR abs/2001.04488 (2020) - 2018
- [i2]Yikang Li, Pak Lun Kevin Ding, Baoxin Li:
Training Neural Networks by Using Power Linear Units (PoLUs). CoRR abs/1802.00212 (2018) - [i1]Pak Lun Kevin Ding, Yikang Li, Baoxin Li:
Mean Local Group Average Precision (mLGAP): A New Performance Metric for Hashing-based Retrieval. CoRR abs/1811.09763 (2018)
Coauthor Index
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