no code implementations • SMM4H (COLING) 2020 • Xiaoyu Zhao, Ying Xiong, Buzhou Tang
This is the system description of the Harbin Institute of Technology Shenzhen (HITSZ) team for the first and second subtasks of the fifth Social Media Mining for Health Applications (SMM4H) shared task in 2020.
no code implementations • 8 Apr 2024 • Jing Ye, Minzhi Fan, XiaoYu Zhang, Shasha Lu, Mengyao Chai, Yunshan Zhang, Xiaoyu Zhao, Shuang Li, Diming Zhang
Graphene based nanomaterials have attracted significant attention for their potentials in biomedical and biotechnology applications in recent years, owing to the outstanding physical and chemical properties.
no code implementations • 23 Jan 2024 • Chuanqing Xu, Kedeng Cheng, Songbai Guo, Dehui Yuan, Xiaoyu Zhao
Based on the analysis of TB infection data, we develop a model of TB transmission dynamics that include potentially infected individuals and BCG vaccination, fit the model parameters to the data on new TB cases, calculate the basic reproduction number \mathcal{R}_v= 0. 4442.
no code implementations • 14 Apr 2023 • Yanfang Lyu, Xiaoyu Zhao, Zhiqiang Gong, Xiao Kang, Wen Yao
Therefore, this work proposes a novel multi-fidelity learning method based on the Fourier Neural Operator by jointing abundant low-fidelity data and limited high-fidelity data under transfer learning paradigm.
1 code implementation • ICCV 2023 • Yutao Cui, Chenkai Zeng, Xiaoyu Zhao, Yichun Yang, Gangshan Wu, LiMin Wang
We expect SportsMOT to encourage the MOT trackers to promote in both motion-based association and appearance-based association.
Ranked #3 on Multi-Object Tracking on SportsMOT (using extra training data)
1 code implementation • 23 Feb 2023 • Yunyang Zhang, Zhiqiang Gong, Xiaoyu Zhao, Wen Yao
Recovering a globally accurate complex physics field from limited sensor is critical to the measurement and control in the aerospace engineering.
1 code implementation • 20 Feb 2023 • Xiaoyu Zhao, Xiaoqian Chen, Zhiqiang Gong, Weien Zhou, Wen Yao, Yunyang Zhang
The MLP embedding is propitious to more sparse input, while the others benefit from spatial information preservation and perform better with the increase of observation data.
no code implementations • 17 Jan 2023 • Yunyang Zhang, Zhiqiang Gong, Weien Zhou, Xiaoyu Zhao, Xiaohu Zheng, Wen Yao
Then, a self-supervised learning method for training the physics-driven deep multi-fidelity model (PD-DMFM) is proposed, which fully utilizes the physics characteristics of the engineering systems and reduces the dependence on large amounts of labeled low-fidelity data in the training process.
no code implementations • 10 Mar 2022 • Yunyang Zhang, Zhiqiang Gong, Xiaohu Zheng, Xiaoyu Zhao, Wen Yao
However, the wrong pseudo labeling information generated by cross supervision would confuse the training process and negatively affect the effectiveness of the segmentation model.
1 code implementation • 8 Mar 2022 • Xiaoyu Zhao, Xiaoqian Chen, Zhiqiang Gong, Wen Yao, Yunyang Zhang, Xiaohu Zheng
This paper proposes a contrastive enhancement approach using latent prototypes to leverage latent classes and raise the utilization of similarity information between prototype and query features.
1 code implementation • 14 Feb 2022 • Xiaohu Zheng, Wen Yao, Zhiqiang Gong, Yunyang Zhang, Xiaoyu Zhao, Tingsong Jiang
However, a lot of labeled data is needed to train CNN, and the common CNN can not quantify the aleatoric uncertainty caused by data noise.
no code implementations • 26 Jan 2022 • Xingwen Peng, Xingchen Li, Zhiqiang Gong, Xiaoyu Zhao, Wen Yao
To solve the problem, this work proposes a novel deep learning method based on patchwise training to reconstruct the temperature field of electronic equipment accurately from limited observation.
1 code implementation • 26 Sep 2021 • Xiaoyu Zhao, Zhiqiang Gong, Yunyang Zhang, Wen Yao, Xiaoqian Chen
As the construction of data pairs in most engineering problems is time-consuming, data acquisition is becoming the predictive capability bottleneck of most deep surrogate models, which also exists in surrogate for thermal analysis and design.
2 code implementations • 17 Aug 2021 • Xiaoqian Chen, Zhiqiang Gong, Xiaoyu Zhao, Weien Zhou, Wen Yao
To overcome this problem, this work develops a machine learning modelling benchmark for TFR-HSS task.
1 code implementation • 9 Jul 2021 • Wei Peng, Jun Zhang, Weien Zhou, Xiaoyu Zhao, Wen Yao, Xiaoqian Chen
Physics Informed Neural Network (PINN) is a scientific computing framework used to solve both forward and inverse problems modeled by Partial Differential Equations (PDEs).
1 code implementation • 20 Mar 2021 • Xianqi Chen, Xiaoyu Zhao, Zhiqiang Gong, Jun Zhang, Weien Zhou, Xiaoqian Chen, Wen Yao
Thermal issue is of great importance during layout design of heat source components in systems engineering, especially for high functional-density products.
no code implementations • 2 Nov 2020 • Feng Cen, Xiaoyu Zhao, Wuzhuang Li, Guanghui Wang
To alleviate the dependency on large-scale occluded image datasets, we propose a novel approach to improve the classification accuracy of occluded images by fine-tuning the pre-trained models with a set of augmented deep feature vectors (DFVs).