1 code implementation • 11 Feb 2024 • Hao Chen, Gonzalo E. Constante Flores, Can Li
The incorporation of physics into neural networks can improve generalization and data efficiency.
1 code implementation • 17 Nov 2023 • Can Li, Sheng Shao, Junyi Qu, Shuchao Pang, Mehmet A. Orgun
However, due to the fact that medical image annotation requires a great deal of manpower and expertise, as well as the fact that clinical departments perform image annotation based on task orientation, there is the problem of having fewer medical image annotation data with more unlabeled data and having many datasets that annotate only a single organ.
no code implementations • 20 Oct 2023 • Can Li, Dejian Lai, Xiaoqian Jiang, Kai Zhang
Liver transplantation often faces fairness challenges across subgroups defined by sensitive attributes like age group, gender, and race/ethnicity.
no code implementations • 30 Sep 2023 • Jiongkang Ni, Xiaoliang Xu, Yuxiang Wang, Can Li, Jiajie Yao, Shihai Xiao, Xuecang Zhang
The main drawback of graph-based ANNS is that a graph index would be too large to fit into the memory especially for a large-scale $\mathcal{X}$.
no code implementations • 29 Sep 2023 • Song Wang, Zhu Wang, Can Li, Xiaojuan Qi, Hayden Kwok-Hay So
In comparison to conventional RGB cameras, the superior temporal resolution of event cameras allows them to capture rich information between frames, making them prime candidates for object tracking.
no code implementations • 23 Aug 2023 • Hao Chen, Gonzalo E. Constante-Flores, Can Li
Decision-making problems can be represented as mathematical optimization models, finding wide applications in fields such as economics, engineering and manufacturing, transportation, and health care.
no code implementations • 19 Aug 2023 • Qunsong Zeng, Jiawei Liu, Mingrui Jiang, Jun Lan, Yi Gong, Zhongrui Wang, Yida Li, Can Li, Jim Ignowski, Kaibin Huang
To support emerging applications ranging from holographic communications to extended reality, next-generation mobile wireless communication systems require ultra-fast and energy-efficient baseband processors.
no code implementations • 16 Jun 2023 • Yuhang Hao, Zengfu Wang, Jing Fu, Xianglong Bai, Can Li, Quan Pan
We track moving targets with a distributed multiple-input multiple-output (MIMO) radar, for which the transmitters and receivers are appropriately paired and selected with a limited number of radar stations.
no code implementations • 5 Apr 2023 • Can Li, Xiaoqian Jiang, Kai Zhang
Specifically, we proposed a deep-learning model to predict multiple risk factors after a liver transplant.
no code implementations • 14 Dec 2022 • Xianglong Bai, Hua Lan, Zengfu Wang, Quan Pan, Yuhang Hao, Can Li
Then, a unified MP algorithm is used to infer the marginal posterior probability distributions of targets, clutter, and data association by splitting the joint probability distribution into a mean-field approximate part and a belief propagation part.
no code implementations • 26 Oct 2022 • Can Li, Lei Bai, Lina Yao, S. Travis Waller, Wei Liu
Transportation is the backbone of the economy and urban development.
1 code implementation • 14 Jul 2022 • Liang Qiao, Hui Jiang, Ying Chen, Can Li, Pengfei Li, Zaisheng Li, Baorui Zou, Dashan Guo, Yingda Xu, Yunlu Xu, Zhanzhan Cheng, Yi Niu
Compared with the previous opensource OCR toolbox, DavarOCR has relatively more complete support for the sub-tasks of the cutting-edge technology of document understanding.
no code implementations • 14 Jul 2022 • Zhanzhan Cheng, Peng Zhang, Can Li, Qiao Liang, Yunlu Xu, Pengfei Li, ShiLiang Pu, Yi Niu, Fei Wu
Most existing methods divide this task into two subparts: the text reading part for obtaining the plain text from the original document images and the information extraction part for extracting key contents.
no code implementations • 8 Jun 2022 • Can Li, Lei Bai, Wei Liu, Lina Yao, S Travis Waller
These multimodal forecasting models can improve accuracy but be less practical when different parts of multimodal datasets are owned by different institutions who cannot directly share data among them.
no code implementations • 15 Apr 2022 • Ruibin Mao, Bo Wen, Yahui Zhao, Arman Kazemi, Ann Franchesca Laguna, Michael Neimier, X. Sharon Hu, Xia Sheng, Catherine E. Graves, John Paul Strachan, Can Li
Memory augmented neural network has been proposed to achieve the goal, but the memory module has to be stored in an off-chip memory due to its size.
no code implementations • 15 Oct 2021 • Pulakesh Upadhyaya, Kai Zhang, Can Li, Xiaoqian Jiang, Yejin Kim
Causal structure learning refers to a process of identifying causal structures from observational data, and it can have multiple applications in biomedicine and health care.
1 code implementation • 13 May 2021 • Peng Zhang, Can Li, Liang Qiao, Zhanzhan Cheng, ShiLiang Pu, Yi Niu, Fei Wu
To address the above limitations, we propose a unified framework VSR for document layout analysis, combining vision, semantics and relations.
Ranked #3 on Document Layout Analysis on PubLayNet val
no code implementations • 20 Nov 2020 • Peng Jia, Mingyang Ma, Dongmei Cai, Weihua Wang, Juanjuan Li, Can Li
However if there exists strong atmospheric turbulence or the brightness of guide stars is low, the accuracy of wavefront measurements will be affected.
no code implementations • 12 Sep 2020 • Can Li, Lei Bai, Wei Liu, Lina Yao, S Travis Waller
Accurate demand forecasting of different public transport modes(e. g., buses and light rails) is essential for public service operation. However, the development level of various modes often varies sig-nificantly, which makes it hard to predict the demand of the modeswith insufficient knowledge and sparse station distribution (i. e., station-sparse mode).
3 code implementations • NeurIPS 2020 • Lei Bai, Lina Yao, Can Li, Xianzhi Wang, Can Wang
We further propose an Adaptive Graph Convolutional Recurrent Network (AGCRN) to capture fine-grained spatial and temporal correlations in traffic series automatically based on the two modules and recurrent networks.
Ranked #2 on Traffic Prediction on BJTaxi
1 code implementation • 30 May 2018 • Can Li, Zhongrui Wang, Mingyi Rao, Daniel Belkin, Wenhao Song, Hao Jiang, Peng Yan, Yunning Li, Peng Lin, Miao Hu, Ning Ge, John Paul Strachan, Mark Barnell, Qing Wu, R. Stanley Williams, J. Joshua Yang, Qiangfei Xia
Recent breakthroughs in recurrent deep neural networks with long short-term memory (LSTM) units has led to major advances in artificial intelligence.
Emerging Technologies Applied Physics