Zobrazeno 1 - 10
of 461
pro vyhledávání: '"Feng Jinchao"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract Breast cancer (BC) significantly contributes to cancer-related mortality in women, underscoring the criticality of early detection for optimal patient outcomes. Mammography is a key tool for identifying and diagnosing breast abnormalities; h
Externí odkaz:
https://doaj.org/article/3e4acbc1dc4e4f3da10f55051a90cbfe
Autor:
Muhammad Yaqub, Feng Jinchao, Shahzad Ahmed, Atif Mehmood, Imran Shabir Chuhan, Malik Abdul Manan, Muhammad Salman Pathan
Publikováno v:
Alexandria Engineering Journal, Vol 76, Iss , Pp 609-627 (2023)
Brain tumors, which are uncontrolled growths of brain cells, pose a threat to people worldwide. However, accurately classifying brain tumors through computerized methods has been difficult due to differences in size, shape, and location of the tumors
Externí odkaz:
https://doaj.org/article/27885af96d8245f6945c5d93c69201f3
Autor:
Muhammad Yaqub, Feng Jinchao, Shahzad Ahmed, Kaleem Arshid, Muhammad Atif Bilal, Muhammad Pervez Akhter, Muhammad Sultan Zia
Publikováno v:
Applied Sciences, Vol 12, Iss 17, p 8841 (2022)
Generative adversarial networks (GAN), which are fueled by deep learning, are an efficient technique for image reconstruction using under-sampled MR data. In most cases, the performance of a particular model’s reconstruction must be improved by usi
Externí odkaz:
https://doaj.org/article/f057a33b9325482591c93369ddb6088d
We present iDARR, a scalable iterative Data-Adaptive RKHS Regularization method, for solving ill-posed linear inverse problems. The method searches for solutions in subspaces where the true solution can be identified, with the data-adaptive RKHS pena
Externí odkaz:
http://arxiv.org/abs/2401.00656
Autor:
Feng, Jinchao, Zhong, Ming
We present a comprehensive examination of learning methodologies employed for the structural identification of dynamical systems. These techniques are designed to elucidate emergent phenomena within intricate systems of interacting agents. Our approa
Externí odkaz:
http://arxiv.org/abs/2311.00875
In this paper, we focus on the data-driven discovery of a general second-order particle-based model that contains many state-of-the-art models for modeling the aggregation and collective behavior of interacting agents of similar size and body type. T
Externí odkaz:
http://arxiv.org/abs/2311.00902
Autor:
Muhammad Shabaan, Kaleem Arshid, Muhammad Yaqub, Feng Jinchao, M. Sultan Zia, Giridhar Reddy Boja, Muazzam Iftikhar, Usman Ghani, Loknath Sai Ambati, Rizwan Munir
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 20, Iss 1, Pp 1-1 (2020)
An amendment to this paper has been published and can be accessed via the original article.
Externí odkaz:
https://doaj.org/article/b148f612f44d4f07b6d622977a8f81d5
Dynamical systems across many disciplines are modeled as interacting particles or agents, with interaction rules that depend on a very small number of variables (e.g. pairwise distances, pairwise differences of phases, etc...), functions of the state
Externí odkaz:
http://arxiv.org/abs/2208.02758
Autor:
Wang, Lei, Zheng, Lamei, Hu, Hao, Qin, Liang, Liu, Haiqiang, Wu, Ran, Ren, Zhentao, Fu, Jinxiang, Xu, Hualei, Guo, Hua, Chen, Lulu, Yang, Chenyu, Feng, Jinchao, Zhou, Yijun, Gao, Fei, Wang, Xiaodong
Publikováno v:
In Industrial Crops & Products 15 November 2024 220
Autor:
Wu, Ran, Jiang, Dongxu, Hu, Hao, Yang, Chenyu, Qin, Liang, Chen, Lulu, Hu, Zehui, Xu, Hualei, Li, Jinrong, Liu, Haiqiang, Guo, Hua, Fu, Jinxiang, Hao, Qichen, Zhou, Yijun, Feng, Jinchao, Wang, Qiang, Wang, Xiaodong
Publikováno v:
In Chinese Chemical Letters November 2024 35(11)