Zobrazeno 1 - 10
of 1 047
pro vyhledávání: '"YU Xiaowei"'
Autor:
YU Xiaowei, KUANG Cuijie
Publikováno v:
发电技术, Vol 43, Iss 2, Pp 367-372 (2022)
Urea pyrolysis technology has been applied in many coal-fired power plants with it's advantages of safety and nontoxicity, but there are problems such as sediment plugging in the application. A 1 000 MW unit with urea pyrolysis system was seriously b
Externí odkaz:
https://doaj.org/article/94851fa85d7f4dad91a006eda0b972e0
Unsupervised domain adaptation (UDA) aims to leverage the knowledge learned from labeled source domains to improve performance on the unlabeled target domains. While Convolutional Neural Networks (CNNs) have been dominant in previous UDA methods, rec
Externí odkaz:
http://arxiv.org/abs/2411.07794
Using Structural Similarity and Kolmogorov-Arnold Networks for Anatomical Embedding of 3-hinge Gyrus
Autor:
Chen, Minheng, Cao, Chao, Chen, Tong, Zhuang, Yan, Zhang, Jing, Lyu, Yanjun, Yu, Xiaowei, Zhang, Lu, Liu, Tianming, Zhu, Dajiang
The 3-hinge gyrus (3HG) is a newly defined folding pattern, which is the conjunction of gyri coming from three directions in cortical folding. Many studies demonstrated that 3HGs can be reliable nodes when constructing brain networks or connectome si
Externí odkaz:
http://arxiv.org/abs/2410.23598
Autor:
Zhong, Tianyang, Liu, Zhengliang, Pan, Yi, Zhang, Yutong, Zhou, Yifan, Liang, Shizhe, Wu, Zihao, Lyu, Yanjun, Shu, Peng, Yu, Xiaowei, Cao, Chao, Jiang, Hanqi, Chen, Hanxu, Li, Yiwei, Chen, Junhao, Hu, Huawen, Liu, Yihen, Zhao, Huaqin, Xu, Shaochen, Dai, Haixing, Zhao, Lin, Zhang, Ruidong, Zhao, Wei, Yang, Zhenyuan, Chen, Jingyuan, Wang, Peilong, Ruan, Wei, Wang, Hui, Zhao, Huan, Zhang, Jing, Ren, Yiming, Qin, Shihuan, Chen, Tong, Li, Jiaxi, Zidan, Arif Hassan, Jahin, Afrar, Chen, Minheng, Xia, Sichen, Holmes, Jason, Zhuang, Yan, Wang, Jiaqi, Xu, Bochen, Xia, Weiran, Yu, Jichao, Tang, Kaibo, Yang, Yaxuan, Sun, Bolun, Yang, Tao, Lu, Guoyu, Wang, Xianqiao, Chai, Lilong, Li, He, Lu, Jin, Sun, Lichao, Zhang, Xin, Ge, Bao, Hu, Xintao, Zhang, Lian, Zhou, Hua, Zhang, Lu, Zhang, Shu, Liu, Ninghao, Jiang, Bei, Kong, Linglong, Xiang, Zhen, Ren, Yudan, Liu, Jun, Jiang, Xi, Bao, Yu, Zhang, Wei, Li, Xiang, Li, Gang, Liu, Wei, Shen, Dinggang, Sikora, Andrea, Zhai, Xiaoming, Zhu, Dajiang, Liu, Tianming
This comprehensive study evaluates the performance of OpenAI's o1-preview large language model across a diverse array of complex reasoning tasks, spanning multiple domains, including computer science, mathematics, natural sciences, medicine, linguist
Externí odkaz:
http://arxiv.org/abs/2409.18486
Autor:
Lyu, Yanjun, Wu, Zihao, Zhang, Lu, Zhang, Jing, Li, Yiwei, Ruan, Wei, Liu, Zhengliang, Yu, Xiaowei, Cao, Chao, Chen, Tong, Chen, Minheng, Zhuang, Yan, Li, Xiang, Liu, Rongjie, Huang, Chao, Li, Wentao, Liu, Tianming, Zhu, Dajiang
Pre-trained large language models(LLMs) have attracted increasing attention in biomedical domains due to their success in natural language processing. However, the complex traits and heterogeneity of multi-sources genomics data pose significant chall
Externí odkaz:
http://arxiv.org/abs/2409.09825
Autor:
Huang, Heng, Zhao, Lin, Wu, Zihao, Yu, Xiaowei, Zhang, Jing, Hu, Xintao, Zhu, Dajiang, Liu, Tianming
Brain decoding techniques are essential for understanding the neurocognitive system. Although numerous methods have been introduced in this field, accurately aligning complex external stimuli with brain activities remains a formidable challenge. To a
Externí odkaz:
http://arxiv.org/abs/2407.09509
Autor:
Ma, Chong, Jiang, Hanqi, Chen, Wenting, Li, Yiwei, Wu, Zihao, Yu, Xiaowei, Liu, Zhengliang, Guo, Lei, Zhu, Dajiang, Zhang, Tuo, Shen, Dinggang, Liu, Tianming, Li, Xiang
In the medical multi-modal frameworks, the alignment of cross-modality features presents a significant challenge. However, existing works have learned features that are implicitly aligned from the data, without considering the explicit relationships
Externí odkaz:
http://arxiv.org/abs/2403.12416
Semi-supervised learning (SSL) seeks to enhance task performance by training on both labeled and unlabeled data. Mainstream SSL image classification methods mostly optimize a loss that additively combines a supervised classification objective with a
Externí odkaz:
http://arxiv.org/abs/2403.10658
Automated interpretation of ultrasound imaging of the heart (echocardiograms) could improve the detection and treatment of aortic stenosis (AS), a deadly heart disease. However, existing deep learning pipelines for assessing AS from echocardiograms h
Externí odkaz:
http://arxiv.org/abs/2403.06024
Autor:
Liu, Zhengliang, Jiang, Hanqi, Zhong, Tianyang, Wu, Zihao, Ma, Chong, Li, Yiwei, Yu, Xiaowei, Zhang, Yutong, Pan, Yi, Shu, Peng, Lyu, Yanjun, Zhang, Lu, Yao, Junjie, Dong, Peixin, Cao, Chao, Xiao, Zhenxiang, Wang, Jiaqi, Zhao, Huan, Xu, Shaochen, Wei, Yaonai, Chen, Jingyuan, Dai, Haixing, Wang, Peilong, He, Hao, Wang, Zewei, Wang, Xinyu, Zhang, Xu, Zhao, Lin, Liu, Yiheng, Zhang, Kai, Yan, Liheng, Sun, Lichao, Liu, Jun, Qiang, Ning, Ge, Bao, Cai, Xiaoyan, Zhao, Shijie, Hu, Xintao, Yuan, Yixuan, Li, Gang, Zhang, Shu, Zhang, Xin, Jiang, Xi, Zhang, Tuo, Shen, Dinggang, Li, Quanzheng, Liu, Wei, Li, Xiang, Zhu, Dajiang, Liu, Tianming
In this paper, we present a large-scale evaluation probing GPT-4V's capabilities and limitations for biomedical image analysis. GPT-4V represents a breakthrough in artificial general intelligence (AGI) for computer vision, with applications in the bi
Externí odkaz:
http://arxiv.org/abs/2312.05256