Zobrazeno 1 - 10
of 143
pro vyhledávání: '"Zhang Qingchao"'
The lightweight Multi-state Constraint Kalman Filter (MSCKF) has been well-known for its high efficiency, in which the delayed update has been usually adopted since its proposal. This work investigates the immediate update strategy of MSCKF based on
Externí odkaz:
http://arxiv.org/abs/2411.02028
Inverse problems arise in many applications, especially tomographic imaging. We develop a Learned Alternating Minimization Algorithm (LAMA) to solve such problems via two-block optimization by synergizing data-driven and classical techniques with pro
Externí odkaz:
http://arxiv.org/abs/2410.21111
We propose a novel Learned Alternating Minimization Algorithm (LAMA) for dual-domain sparse-view CT image reconstruction. LAMA is naturally induced by a variational model for CT reconstruction with learnable nonsmooth nonconvex regularizers, which ar
Externí odkaz:
http://arxiv.org/abs/2306.02644
Generating multi-contrasts/modal MRI of the same anatomy enriches diagnostic information but is limited in practice due to excessive data acquisition time. In this paper, we propose a novel deep-learning model for joint reconstruction and synthesis o
Externí odkaz:
http://arxiv.org/abs/2204.03804
Purpose: This work aims at developing a generalizable MRI reconstruction model in the meta-learning framework. The standard benchmarks in meta-learning are challenged by learning on diverse task distributions. The proposed network learns the regulari
Externí odkaz:
http://arxiv.org/abs/2110.00715
Publikováno v:
In Heliyon 30 August 2024 10(16)
Autor:
Zhao, Zhou, Zhang, Zengxing, Guo, Rui, Shi, Weipeng, Zhang, Qingchao, Guo, Yuzhen, Wang, Yonghua, Liu, Dan, Xue, Chenyang
Publikováno v:
In Materials Today Communications August 2024 40
We propose a provably convergent method, called Efficient Learned Descent Algorithm (ELDA), for low-dose CT (LDCT) reconstruction. ELDA is a highly interpretable neural network architecture with learned parameters and meanwhile retains convergence gu
Externí odkaz:
http://arxiv.org/abs/2104.12939
Autor:
Ren, Delun, Xu, Ting, Yan, Hao, Zhang, Xinyang, Li, Ze, Li, Yue, Leng, Jun, Zhang, Qingchao, Li, Jinming, Zhao, Deming, Shi, Huibing, Jiang, Haiying, Liu, Yibin, Chen, Xiaobo, Yang, Chaohe
Publikováno v:
In Microporous and Mesoporous Materials 15 January 2024 364
Publikováno v:
Advances in Visual Computing. ISVC 2020. Lecture Notes in Computer Science
We present an algorithm for multi-scale tumor (chimeric cell) detection in high resolution slide scans. The broad range of tumor sizes in our dataset pose a challenge for current Convolutional Neural Networks (CNN) which often fail when image feature
Externí odkaz:
http://arxiv.org/abs/2010.00641