Search Results for author: Can Li

Found 21 papers, 6 papers with code

Physics-Informed Neural Networks with Hard Linear Equality Constraints

1 code implementation11 Feb 2024 Hao Chen, Gonzalo E. Constante Flores, Can Li

The incorporation of physics into neural networks can improve generalization and data efficiency.

UniMOS: A Universal Framework For Multi-Organ Segmentation Over Label-Constrained Datasets

1 code implementation17 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.

Image Segmentation Medical Image Segmentation +3

FERI: A Multitask-based Fairness Achieving Algorithm with Applications to Fair Organ Transplantation

no code implementations20 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.


DiskANN++: Efficient Page-based Search over Isomorphic Mapped Graph Index using Query-sensitivity Entry Vertex

no code implementations30 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 $\mathcal{X}$.


SpikeMOT: Event-based Multi-Object Tracking with Sparse Motion Features

no code implementations29 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.

Multi-Object Tracking Object

Diagnosing Infeasible Optimization Problems Using Large Language Models

no code implementations23 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.

Chatbot Decision Making +1

Realizing In-Memory Baseband Processing for Ultra-Fast and Energy-Efficient 6G

no code implementations19 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.

Combinatorial-restless-bandit-based Transmitter-Receiver Online Selection for Distributed MIMO Radars With Non-Stationary Channels

no code implementations16 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.

Robust Multitarget Tracking in Interference Environments: A Message-Passing Approach

no code implementations14 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.

DavarOCR: A Toolbox for OCR and Multi-Modal Document Understanding

1 code implementation14 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.

document understanding Optical Character Recognition (OCR)

TRIE++: Towards End-to-End Information Extraction from Visually Rich Documents

no code implementations14 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.

Language Modelling

Unsupervised Knowledge Adaptation for Passenger Demand Forecasting

no code implementations8 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.

Experimentally realized memristive memory augmented neural network

no code implementations15 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.

One-Shot Learning

Scalable Causal Structure Learning: Scoping Review of Traditional and Deep Learning Algorithms and New Opportunities in Biomedicine

no code implementations15 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.

BIG-bench Machine Learning Causal Discovery +1

VSR: A Unified Framework for Document Layout Analysis combining Vision, Semantics and Relations

1 code implementation13 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.

Document Layout Analysis Relation

Compressive Shack-Hartmann Wavefront Sensor based on Deep Neural Networks

no code implementations20 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.

Compressive Sensing Image Deconvolution +1

Knowledge Adaption for Demand Prediction based on Multi-task Memory Neural Network

no code implementations12 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).

Multi-Task Learning

Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting

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.

Graph Generation Multivariate Time Series Forecasting +4

Long short-term memory networks in memristor crossbars

1 code implementation30 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

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