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2020 – today
- 2024
[j20]Sarthak Pati
, Sourav Kumar, Amokh Varma, Brandon Edwards, Charles Lu, Liangqiong Qu, Justin J. Wang, Anantharaman Lakshminarayanan, Shih-han Wang, Micah J. Sheller, Ken Chang, Praveer Singh, Daniel L. Rubin, Jayashree Kalpathy-Cramer, Spyridon Bakas:
Privacy preservation for federated learning in health care. Patterns 5(7): 100974 (2024)- [j19]Weihong Ren, Jinguo Luo, Weibo Jiang, Liangqiong Qu, Zhi Han, Jiandong Tian, Honghai Liu:
Learning Self- and Cross-Triplet Context Clues for Human-Object Interaction Detection. IEEE Trans. Circuits Syst. Video Technol. 34(10): 9760-9773 (2024) - [j18]Tianlei Ma, Qi Ma, Zhen Yang, Jing J. Liang, Jun Fu, Yu Dou, Yanan Ku, Usman Ahmad, Liangqiong Qu:
MCDNet: An Infrared Small Target Detection Network Using Multi-Criteria Decision and Adaptive Labeling Strategy. IEEE Trans. Geosci. Remote. Sens. 62: 1-14 (2024) - [j17]Peiran Xu, Zeyu Wang, Jieru Mei, Liangqiong Qu, Alan L. Yuille, Cihang Xie, Yuyin Zhou:
FedConv: Enhancing Convolutional Neural Networks for Handling Data Heterogeneity in Federated Learning. Trans. Mach. Learn. Res. 2024 (2024) - [c16]Weibo Jiang, Weihong Ren, Jiandong Tian, Liangqiong Qu, Zhiyong Wang, Honghai Liu:
Exploring Self- and Cross-Triplet Correlations for Human-Object Interaction Detection. AAAI 2024: 2543-2551 - [c15]Jiawei Liu, Qiang Wang, Huijie Fan, Yinong Wang, Yandong Tang, Liangqiong Qu:
Residual Denoising Diffusion Models. CVPR 2024: 2773-2783 - [c14]Zhiheng Cheng, Qingyue Wei, Hongru Zhu, Yan Wang, Liangqiong Qu, Wei Shao, Yuyin Zhou:
Unleashing the Potential of SAM for Medical Adaptation via Hierarchical Decoding. CVPR 2024: 3511-3522 - [c13]Junyuan Zhang, Shuang Zeng, Miao Zhang, Runxi Wang, Feifei Wang, Yuyin Zhou, Paul Pu Liang, Liangqiong Qu:
FLHetBench: Benchmarking Device and State Heterogeneity in Federated Learning. CVPR 2024: 12098-12108 - [c12]Chengxin Zheng, Junzhong Ji, Yanzhao Shi, Xiaodan Zhang, Liangqiong Qu:
See Detail Say Clear: Towards Brain CT Report Generation via Pathological Clue-driven Representation Learning. EMNLP (Findings) 2024: 16542-16552 - [c11]Sharut Gupta, Ken Chang, Liangqiong Qu, Aakanksha Rana, Syed Rakin Ahmed, Mehak Aggarwal, Nishanth Thumbavanam Arun, Ashwin Vaswani, Shruti Raghavan, Vibha Agarwal, Mishka Gidwani, Katharina Hoebel, Jay B. Patel, Charles Lu, Christopher P. Bridge, Daniel L. Rubin, Jayashree Kalpathy-Cramer, Praveer Singh:
Addressing Catastrophic Forgetting by Modulating Global Batch Normalization Statistics for Medical Domain Expansion. AIPAD/PILM@MICCAI 2024: 57-72 - [c10]Shuang Zeng, Pengxin Guo, Shuai Wang, Jianbo Wang, Yuyin Zhou, Liangqiong Qu:
Tackling Data Heterogeneity in Federated Learning via Loss Decomposition. MICCAI (10) 2024: 707-717 - [i22]Weibo Jiang, Weihong Ren, Jiandong Tian, Liangqiong Qu, Zhiyong Wang, Honghai Liu:
Exploring Self- and Cross-Triplet Correlations for Human-Object Interaction Detection. CoRR abs/2401.05676 (2024) - [i21]Zhiheng Cheng, Qingyue Wei, Hongru Zhu, Yan Wang, Liangqiong Qu, Wei Shao, Yuyin Zhou:
Unleashing the Potential of SAM for Medical Adaptation via Hierarchical Decoding. CoRR abs/2403.18271 (2024) - [i20]Shuang Zeng, Pengxin Guo, Shuai Wang, Jianbo Wang, Yuyin Zhou, Liangqiong Qu:
Tackling Data Heterogeneity in Federated Learning via Loss Decomposition. CoRR abs/2408.12300 (2024) - [i19]Chengxin Zheng, Junzhong Ji, Yanzhao Shi, Xiaodan Zhang, Liangqiong Qu:
See Detail Say Clear: Towards Brain CT Report Generation via Pathological Clue-driven Representation Learning. CoRR abs/2409.19676 (2024) - [i18]Pengxin Guo, Shuang Zeng, Yanran Wang, Huijie Fan, Feifei Wang, Liangqiong Qu:
Selective Aggregation for Low-Rank Adaptation in Federated Learning. CoRR abs/2410.01463 (2024) - 2023
- [j16]Rui Yan, Liangqiong Qu, Qingyue Wei, Shih-Cheng Huang, Liyue Shen, Daniel L. Rubin, Lei Xing, Yuyin Zhou:
Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging. IEEE Trans. Medical Imaging 42(7): 1932-1943 (2023) - [j15]Jiawei Liu, Qiang Wang, Huijie Fan, Wentao Li, Liangqiong Qu, Yandong Tang:
A Decoupled Multi-Task Network for Shadow Removal. IEEE Trans. Multim. 25: 9449-9463 (2023) - [j14]Shuai Wang, Kun Sun, Li Wang, Liangqiong Qu, Fuhua Yan, Qian Wang, Dinggang Shen:
Breast Tumor Segmentation in DCE-MRI With Tumor Sensitive Synthesis. IEEE Trans. Neural Networks Learn. Syst. 34(8): 4990-5001 (2023) - [c9]Siyi Tang, Jared A. Dunnmon, Liangqiong Qu, Khaled Kamal Saab, Tina Baykaner, Christopher Lee-Messer, Daniel L. Rubin:
Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space Models. CHIL 2023: 50-71 - [c8]Yanzhao Shi, Junzhong Ji, Xiaodan Zhang, Liangqiong Qu, Ying Liu:
Granularity Matters: Pathological Graph-driven Cross-modal Alignment for Brain CT Report Generation. EMNLP 2023: 6617-6630 - [i17]Jiawei Liu, Qiang Wang, Huijie Fan, Yinong Wang, Yandong Tang, Liangqiong Qu:
Residual Denoising Diffusion Models. CoRR abs/2308.13712 (2023) - [i16]Peiran Xu, Zeyu Wang, Jieru Mei, Liangqiong Qu, Alan L. Yuille, Cihang Xie, Yuyin Zhou:
FedConv: Enhancing Convolutional Neural Networks for Handling Data Heterogeneity in Federated Learning. CoRR abs/2310.04412 (2023) - [i15]Xingru Huang, Yihao Guo, Jian Huang, Zhi Li, Tianyun Zhang, Kunyan Cai, Gaopeng Huang, Wenhao Chen, Zhaoyang Xu, Liangqiong Qu, Ji Hu, Tingyu Wang, Shaowei Jiang, Chenggang Yan, Yaoqi Sun, Xin Ye, Yaqi Wang:
DEFN: Dual-Encoder Fourier Group Harmonics Network for Three-Dimensional Macular Hole Reconstruction with Stochastic Retinal Defect Augmentation and Dynamic Weight Composition. CoRR abs/2311.00483 (2023) - 2022
- [j13]Junzhong Ji, Mingzhan Wang, Xiaodan Zhang, Minglong Lei, Liangqiong Qu:
Relation constraint self-attention for image captioning. Neurocomputing 501: 778-789 (2022) - [j12]Jie Wei, Zhengwang Wu, Li Wang, Toan Duc Bui, Liangqiong Qu, Pew-Thian Yap, Yong Xia, Gang Li, Dinggang Shen:
A cascaded nested network for 3T brain MR image segmentation guided by 7T labeling. Pattern Recognit. 124: 108420 (2022) - [j11]Miao Zhang, Liangqiong Qu, Praveer Singh, Jayashree Kalpathy-Cramer, Daniel L. Rubin:
SplitAVG: A Heterogeneity-Aware Federated Deep Learning Method for Medical Imaging. IEEE J. Biomed. Health Informatics 26(9): 4635-4644 (2022) - [c7]Liangqiong Qu, Yuyin Zhou, Paul Pu Liang, Yingda Xia, Feifei Wang, Ehsan Adeli, Li Fei-Fei, Daniel L. Rubin:
Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning. CVPR 2022: 10051-10061 - [i14]Yan-Ran Wang, Liangqiong Qu, Natasha Diba Sheybani, Xiaolong Luo, Jiangshan Wang, Kristina Elizabeth Hawk, Ashok Joseph Theruvath, Sergios Gatidis, Xuerong Xiao, Allison Pribnow, Daniel L. Rubin, Heike E. Daldrup-Link:
Masked Co-attentional Transformer reconstructs 100x ultra-fast/low-dose whole-body PET from longitudinal images and anatomically guided MRI. CoRR abs/2205.04044 (2022) - [i13]Rui Yan, Liangqiong Qu, Qingyue Wei, Shih-Cheng Huang, Liyue Shen, Daniel L. Rubin, Lei Xing, Yuyin Zhou:
Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging. CoRR abs/2205.08576 (2022) - [i12]Siyi Tang, Jared A. Dunnmon, Liangqiong Qu, Khaled Kamal Saab, Christopher Lee-Messer, Daniel L. Rubin:
Spatiotemporal Modeling of Multivariate Signals With Graph Neural Networks and Structured State Space Models. CoRR abs/2211.11176 (2022) - 2021
- [j10]Siyuan Liu, Kim-Han Thung, Liangqiong Qu, Weili Lin, Dinggang Shen, Pew-Thian Yap:
Learning MRI artefact removal with unpaired data. Nat. Mach. Intell. 3(1): 60-67 (2021) - [j9]Siyuan Liu, Kim-Han Thung, Liangqiong Qu, Weili Lin, Dinggang Shen, Pew-Thian Yap:
Publisher Correction: Learning MRI artefact removal with unpaired data. Nat. Mach. Intell. 3(2): 181 (2021) - [j8]Shuai Wang, Yang Cong, Hancan Zhu, Xianyi Chen, Liangqiong Qu, Huijie Fan, Qiang Zhang, Mingxia Liu:
Multi-Scale Context-Guided Deep Network for Automated Lesion Segmentation With Endoscopy Images of Gastrointestinal Tract. IEEE J. Biomed. Health Informatics 25(2): 514-525 (2021) - [i11]Sharut Gupta, Praveer Singh, Ken Chang, Liangqiong Qu, Mehak Aggarwal, Nishanth Thumbavanam Arun, Ashwin Vaswani, Shruti Raghavan, Vibha Agarwal, Mishka Gidwani, Katharina Hoebel, Jay B. Patel, Charles Lu, Christopher P. Bridge, Daniel L. Rubin, Jayashree Kalpathy-Cramer:
Addressing catastrophic forgetting for medical domain expansion. CoRR abs/2103.13511 (2021) - [i10]Liangqiong Qu, Yuyin Zhou, Paul Pu Liang, Yingda Xia, Feifei Wang, Li Fei-Fei, Ehsan Adeli, Daniel L. Rubin:
Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning. CoRR abs/2106.06047 (2021) - [i9]Liangqiong Qu, Niranjan Balachandar, Miao Zhang, Daniel L. Rubin:
Handling Data Heterogeneity with Generative Replay in Collaborative Learning for Medical Imaging. CoRR abs/2106.13208 (2021) - [i8]Miao Zhang, Liangqiong Qu, Praveer Singh, Jayashree Kalpathy-Cramer, Daniel L. Rubin:
SplitAVG: A heterogeneity-aware federated deep learning method for medical imaging. CoRR abs/2107.02375 (2021) - [i7]Liangqiong Qu, Niranjan Balachandar, Daniel L. Rubin:
An Experimental Study of Data Heterogeneity in Federated Learning Methods for Medical Imaging. CoRR abs/2107.08371 (2021) - [i6]Siyuan Liu, Kim-Han Thung, Liangqiong Qu, Weili Lin, Dinggang Shen, Pew-Thian Yap:
Learning MRI Artifact Removal With Unpaired Data. CoRR abs/2110.04604 (2021) - 2020
- [j7]Liangqiong Qu, Yongqin Zhang, Shuai Wang, Pew-Thian Yap, Dinggang Shen:
Synthesized 7T MRI from 3T MRI via deep learning in spatial and wavelet domains. Medical Image Anal. 62: 101663 (2020) - [j6]Shuai Wang, Qian Wang, Yeqin Shao, Liangqiong Qu, Chunfeng Lian, Jun Lian, Dinggang Shen:
Iterative Label Denoising Network: Segmenting Male Pelvic Organs in CT From 3D Bounding Box Annotations. IEEE Trans. Biomed. Eng. 67(10): 2710-2720 (2020) - [j5]Shuai Wang, Dong Nie, Liangqiong Qu, Yeqin Shao, Jun Lian, Qian Wang, Dinggang Shen:
CT Male Pelvic Organ Segmentation via Hybrid Loss Network With Incomplete Annotation. IEEE Trans. Medical Imaging 39(6): 2151-2162 (2020) - [c6]Holger R. Roth, Ken Chang, Praveer Singh, Nir Neumark, Wenqi Li, Vikash Gupta, Sharut Gupta, Liangqiong Qu, Alvin Ihsani, Bernardo C. Bizzo, Yuhong Wen, Varun Buch, Meesam Shah, Felipe Kitamura, Matheus Mendonça, Vitor Lavor, Ahmed Harouni, Colin Compas, Jesse Tetreault, Prerna Dogra, Yan Cheng, Selnur Erdal, Richard D. White, Behrooz Hashemian, Thomas J. Schultz, Miao Zhang, Adam McCarthy, B. Min Yun, Elshaimaa Sharaf, Katharina Viktoria Hoebel, Jay B. Patel, Bryan Chen, Sean Ko, Evan Leibovitz, Etta D. Pisano, Laura Coombs, Daguang Xu, Keith J. Dreyer, Ittai Dayan, Ram C. Naidu, Mona Flores, Daniel L. Rubin, Jayashree Kalpathy-Cramer:
Federated Learning for Breast Density Classification: A Real-World Implementation. DART/DCL@MICCAI 2020: 181-191 - [d1]Siyuan Liu, Kim-Han Thung, Liangqiong Qu, Weili Lin, Dinggang Shen, Pew-Thian Yap:
Code used in article "Learning MRI artefact removal with unpaired data". Zenodo, 2020
- [i5]Holger R. Roth, Ken Chang, Praveer Singh, Nir Neumark, Wenqi Li, Vikash Gupta, Sharut Gupta, Liangqiong Qu, Alvin Ihsani, Bernardo C. Bizzo, Yuhong Wen, Varun Buch, Meesam Shah, Felipe Kitamura, Matheus Mendonça, Vitor Lavor, Ahmed Harouni, Colin Compas, Jesse Tetreault, Prerna Dogra, Yan Cheng, Selnur Erdal, Richard D. White, Behrooz Hashemian, Thomas J. Schultz, Miao Zhang, Adam McCarthy, B. Min Yun, Elshaimaa Sharaf, Katharina Viktoria Hoebel, Jay B. Patel, Bryan Chen, Sean Ko, Evan Leibovitz, Etta D. Pisano, Laura Coombs, Daguang Xu, Keith J. Dreyer, Ittai Dayan, Ram C. Naidu, Mona Flores, Daniel L. Rubin, Jayashree Kalpathy-Cramer:
Federated Learning for Breast Density Classification: A Real-World Implementation. CoRR abs/2009.01871 (2020) - [i4]Sharut Gupta, Praveer Singh, Ken Chang, Mehak Aggarwal, Nishanth Thumbavanam Arun, Liangqiong Qu, Katharina Hoebel, Jay B. Patel, Mishka Gidwani, Ashwin Vaswani, Daniel L. Rubin, Jayashree Kalpathy-Cramer:
The unreasonable effectiveness of Batch-Norm statistics in addressing catastrophic forgetting across medical institutions. CoRR abs/2011.08096 (2020)
2010 – 2019
- 2019
- [c5]Liangqiong Qu, Shuai Wang, Pew-Thian Yap, Dinggang Shen:
Wavelet-based Semi-supervised Adversarial Learning for Synthesizing Realistic 7T from 3T MRI. MICCAI (4) 2019: 786-794 - 2018
- [j4]Liangqiong Qu, Jiandong Tian, Huijie Fan, Wentao Li, Yandong Tang:
Evaluation of shadow features. IET Comput. Vis. 12(1): 95-103 (2018) - 2017
- [j3]Zhi Han, Jiandong Tian, Liangqiong Qu, Yandong Tang:
A New Intrinsic-Lighting Color Space for Daytime Outdoor Images. IEEE Trans. Image Process. 26(2): 1031-1039 (2017) - [j2]Liangqiong Qu, Shengfeng He, Jiawei Zhang, Jiandong Tian, Yandong Tang, Qingxiong Yang:
RGBD Salient Object Detection via Deep Fusion. IEEE Trans. Image Process. 26(5): 2274-2285 (2017) - [c4]Liangqiong Qu, Jiandong Tian, Shengfeng He, Yandong Tang, Rynson W. H. Lau:
DeshadowNet: A Multi-context Embedding Deep Network for Shadow Removal. CVPR 2017: 2308-2316 - [c3]Jiawei Zhang, Jianbo Jiao, Mingliang Chen, Liangqiong Qu, Xiaobin Xu, Qingxiong Yang:
A hand pose tracking benchmark from stereo matching. ICIP 2017: 982-986 - 2016
- [j1]Jiandong Tian, Xiaojun Qi, Liangqiong Qu, Yandong Tang:
New spectrum ratio properties and features for shadow detection. Pattern Recognit. 51: 85-96 (2016) - [i3]Liangqiong Qu, Shengfeng He, Jiawei Zhang, Jiandong Tian, Yandong Tang, Qingxiong Yang:
RGBD Salient Object Detection via Deep Fusion. CoRR abs/1607.03333 (2016) - [i2]Jiawei Zhang, Jianbo Jiao, Mingliang Chen, Liangqiong Qu, Xiaobin Xu, Qingxiong Yang:
3D Hand Pose Tracking and Estimation Using Stereo Matching. CoRR abs/1610.07214 (2016) - 2015
- [c2]Zhigang Duan, Jiandong Tian, Liangqiong Qu, Yandong Tang, Yang Cong:
Shadow generation on an image based on tricolor linear attenuation model. ICICS 2015: 1-5 - [c1]Liangqiong Qu, Zhigang Duan, Jiandong Tian, Zhi Han, Yandong Tang:
Object Color Constancy for Outdoor Multiple Light Sources. CCCV (2) 2015: 369-378 - 2014
- [i1]Liangqiong Qu, Jiandong Tian, Zhi Han, Yandong Tang:
Pixel-wise Orthogonal Decomposition for Color Illumination Invariant and Shadow-free Image. CoRR abs/1407.0010 (2014)
Coauthor Index
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last updated on 2024-11-15 19:35 CET by the dblp team
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