Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Yuchen Bi"'
Autor:
Yankai Luo, Yuchen Bi, Ziyun Xu, Linxian Shan, Jun He, Kedan Wang, Zhengjiang Zhou, Lihui Yu, Xingjiao Jiang, Jiangrui Yang, Lijun Yu, Rui Gao, Jingran Wei, Xiaocui Du, Yan Liu, Chongye Fang
Publikováno v:
Frontiers in Veterinary Science, Vol 10 (2024)
White-feather broiler chickens are the dominant species in global poultry meat production. Yet there is growing concern about their health, quality, and growth efficiency. While feed additives, often antibiotics or synthetic chemicals, are used to ma
Externí odkaz:
https://doaj.org/article/a4d31cf0fbe34a3e883c8492b926d22c
In this paper, we study the blow-up analysis for a sequence of solutions to the Liouville type equation with exponential Neumann boundary condition. For interior case, i.e. the blow-up point is an interior point, Li \cite{Li} gave a uniform asymptoti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7902c8b08b4bc9ea51d99df409dd3cbf
Publikováno v:
Systems, Vol 11, Iss 7, p 330 (2023)
Over the past two decades, there has been a surge in digital innovation. China is the world’s second-largest digital economy entity and the national strategy to build a digital China is in full swing. Chinese enterprises have received great support
Externí odkaz:
https://doaj.org/article/9da93a86cd6a40fca38852da53f25129
Publikováno v:
Applied Sciences, Vol 13, Iss 9, p 5260 (2023)
With the increasing popularity of deep learning, enterprises are replacing traditional inefficient and non-robust defect detection methods with intelligent recognition technology. This paper utilizes TL (transfer learning) to enhance the model’s re
Externí odkaz:
https://doaj.org/article/21ae1fcd78cd4c2d922c74d36e0e2a00
Publikováno v:
Frontiers in Computer Science, Vol 2 (2021)
Pauses, disfluencies and language problems in Alzheimer’s disease can be naturally modeled by fine-tuning Transformer-based pre-trained language models such as BERT and ERNIE. Using this method with pause-encoded transcripts, we achieved 89.6% accu
Externí odkaz:
https://doaj.org/article/4859c0283bd246c0921f3ad7b421a11a
Autor:
Lei Du, Yaqin Sun, Shuo Chen, Jiedong Feng, Yindi Zhao, Zhigang Yan, Xuewei Zhang, Yuchen Bian
Publikováno v:
Agriculture, Vol 12, Iss 2, p 248 (2022)
The conventional method for crop insect detection based on visual judgment of the field is time-consuming, laborious, subjective, and error prone. The early detection and accurate localization of agricultural insect pests can significantly improve th
Externí odkaz:
https://doaj.org/article/78e4687a0bc14b588ee80ddba1fe3e9a