Zobrazeno 1 - 10
of 4 390
pro vyhledávání: '"Chuanfu An"'
Dynamic positron emission tomography (PET) images can reveal the distribution of tracers in the organism and the dynamic processes involved in biochemical reactions, and it is widely used in clinical practice. Despite the high effectiveness of dynami
Externí odkaz:
http://arxiv.org/abs/2410.22674
Autor:
Lyu, Kang, Yang, Chuanfu
In this paper, we consider Schr\"odinger operators on $L^2(0,\infty)$ given by \begin{align} Hu=(H_0+V)u=-u^{\prime\prime}+V_0u+Vu=Eu,\nonumber \end{align} where $V_0$ is real, $1$-periodic and $V$ is the perturbation. It is well known that under per
Externí odkaz:
http://arxiv.org/abs/2410.09509
The Hadamard product of tensor train (TT) tensors is one of the most fundamental nonlinear operations in scientific computing and data analysis. Due to its tendency to significantly increase TT ranks, the Hadamard product presents a major computation
Externí odkaz:
http://arxiv.org/abs/2410.04385
Autor:
Wang, Xiao, Wang, Fuling, Li, Yuehang, Ma, Qingchuan, Wang, Shiao, Jiang, Bo, Li, Chuanfu, Tang, Jin
X-ray image-based medical report generation (MRG) is a pivotal area in artificial intelligence which can significantly reduce diagnostic burdens and patient wait times. Despite significant progress, we believe that the task has reached a bottleneck d
Externí odkaz:
http://arxiv.org/abs/2410.00379
A method for successive synthesis of the Weyl matrix on the square lattice is proposed. It allows one to compute the Weyl matrix of a large graph by adding new edges and solving elementary systems of linear algebraic equations at each step. Synthesis
Externí odkaz:
http://arxiv.org/abs/2408.15285
Inspired by the tremendous success of Large Language Models (LLMs), existing X-ray medical report generation methods attempt to leverage large models to achieve better performance. They usually adopt a Transformer to extract the visual features of a
Externí odkaz:
http://arxiv.org/abs/2408.09743
The label annotations for chest X-ray image rib segmentation are time consuming and laborious, and the labeling quality heavily relies on medical knowledge of annotators. To reduce the dependency on annotated data, existing works often utilize genera
Externí odkaz:
http://arxiv.org/abs/2407.15903
Autor:
Zhu, Qianchao, Duan, Jiangfei, Chen, Chang, Liu, Siran, Li, Xiuhong, Feng, Guanyu, Lv, Xin, Cao, Huanqi, Chuanfu, Xiao, Zhang, Xingcheng, Lin, Dahua, Yang, Chao
Large language models (LLMs) now support extremely long context windows, but the quadratic complexity of vanilla attention results in significantly long Time-to-First-Token (TTFT) latency. Existing approaches to address this complexity require additi
Externí odkaz:
http://arxiv.org/abs/2406.15486
Solving the Boltzmann-BGK equation with traditional numerical methods suffers from high computational and memory costs due to the curse of dimensionality. In this paper, we propose a novel accuracy-preserved tensor-train (APTT) method to efficiently
Externí odkaz:
http://arxiv.org/abs/2405.12524
Autor:
Fan, Chao, Hou, Saihui, Liang, Junhao, Shen, Chuanfu, Ma, Jingzhe, Jin, Dongyang, Huang, Yongzhen, Yu, Shiqi
Gait recognition, a rapidly advancing vision technology for person identification from a distance, has made significant strides in indoor settings. However, evidence suggests that existing methods often yield unsatisfactory results when applied to ne
Externí odkaz:
http://arxiv.org/abs/2405.09138