Zobrazeno 1 - 10
of 1 913
pro vyhledávání: '"MENG Ran"'
Publikováno v:
智慧农业, Vol 6, Iss 2, Pp 28-39 (2024)
ObjectiveIn recent years, there has been a significant increase in the severity of leaf diseases in maize, with a noticeable trend of mixed occurrence. This poses a serious threat to the yield and quality of maize. However, there is a lack of studies
Externí odkaz:
https://doaj.org/article/3540beb9458a4b6ebb1278bf547fccd6
Publikováno v:
PLoS ONE, Vol 19, Iss 5 (2024)
Externí odkaz:
https://doaj.org/article/18df6cada465438892efaa4d783ac576
Autor:
Zhou Longfei, Meng Ran, Yu Xing, Liao Yigui, Huang Zehua, Lü Zhengang, Xu Binyuan, Yang Guodong, Peng Shaobing, Xu Le
Publikováno v:
Rice Science, Vol 30, Iss 3, Pp 247-256 (2023)
Pre-harvest yield prediction of ratoon rice is critical for guiding crop interventions in precision agriculture. However, the unique agronomic practice (i.e., varied stubble height treatment) in rice ratooning could lead to inconsistent rice phenolog
Externí odkaz:
https://doaj.org/article/5d8adbbc57e540658644c2681d44f2c1
Autor:
Meng Ran, Chao Zhao, Xiang Xu, Xiao Kong, Younghee Lee, Wenjun Cui, Zhi-Yi Hu, Alexander Roxas, Zhengtang Luo, Huiqiao Li, Feng Ding, Lin Gan, Tianyou Zhai
Publikováno v:
Fundamental Research, Vol 2, Iss 3, Pp 456-461 (2022)
In-plane anisotropy (IPA) due to asymmetry in lattice structures provides an additional parameter for the precise tuning of characteristic polarization-dependent properties in two-dimensional (2D) materials, but the narrow range within which such met
Externí odkaz:
https://doaj.org/article/e0336c807df84eddbb32f7ce17060234
We introduce Integer Scale, a novel post-training quantization scheme for large language models that effectively resolves the inference bottleneck in current fine-grained quantization approaches while maintaining similar accuracies. Integer Scale is
Externí odkaz:
http://arxiv.org/abs/2405.14597
Autor:
Li, Qingyuan, Meng, Ran, Li, Yiduo, Zhang, Bo, Li, Liang, Lu, Yifan, Chu, Xiangxiang, Sun, Yerui, Xie, Yuchen
The large language model era urges faster and less costly inference. Prior model compression works on LLMs tend to undertake a software-centric approach primarily focused on the simulated quantization performance. By neglecting the feasibility of dep
Externí odkaz:
http://arxiv.org/abs/2311.09550
The challenges faced by text classification with large tag systems in natural language processing tasks include multiple tag systems, uneven data distribution, and high noise. To address these problems, the ESimCSE unsupervised comparative learning a
Externí odkaz:
http://arxiv.org/abs/2304.13140
Autor:
Wu, Zhe1 (AUTHOR) bhswuzhe26@sina.com, Meng, Ran1 (AUTHOR) bhsmr008@sina.com, Feng, Wei1 (AUTHOR) fengwei522106@sina.com, Li, Zhaojia1,2 (AUTHOR) tofriendzhaojia@sina.com, Lu, Xuelin1 (AUTHOR) bhslxl1972@sina.com, Chen, Yue1 (AUTHOR) bhscy0901@sohu.com, Deng, Xian3 (AUTHOR) xdeng@genetics.ac.cn, Chen, Tiecheng4 (AUTHOR) ftbchengz@sohu.com, Xue, Zhizhong1 (AUTHOR) nvtw_306675@sohu.com, Wang, Xiuping1 (AUTHOR) bhswxp@163.com
Publikováno v:
Agronomy. Sep2024, Vol. 14 Issue 9, p2139. 14p.
Autor:
Xu, Yi-fan, Sun, Wan-chang, Liu, Er-Yong, Zhou, Meng-ran, Zhang, Bo, Cai, Hui, Zhang, Jing-li
Publikováno v:
In Diamond & Related Materials November 2024 149
Autor:
Xu, Yue, He, Chunfeng, Fan, Jiayao, Zhou, Yuan, Cheng, Chunxiao, Meng, Ran, Cui, Ya, Li, Wei, Gamazon, Eric R., Zhou, Dan
Publikováno v:
In eBioMedicine September 2024 107