Zobrazeno 1 - 10
of 165
pro vyhledávání: '"Zheng Huabin"'
Publikováno v:
Guoji Yanke Zazhi, Vol 24, Iss 6, Pp 990-993 (2024)
AIM: To compare the efficacy of different dosing regimens of conbercept in the treatment of pathological myopic choroidal neovascularization(CNV).METHODS: Prospective clinical study. Totally 42 patients(42 eyes)who were diagnosed with pathological my
Externí odkaz:
https://doaj.org/article/06838196c10d49aa812ec063d273bcf4
Autor:
ZOU Dan, TANG Qiyuan, LIU Longsheng, MAO Ruiqing, ZHENG Huabin, KUANG Na, ZHANG Ming, LIU Hong
Publikováno v:
Guan'gai paishui xuebao, Vol 42, Iss 4, Pp 15-21 (2023)
【Objective】 Transplant is a cultivation commonly used in ratooning rice production in southern China and other eastern Asian countries. Its impact on rice growth and yield depends on a range of factors. This paper presents an experimental study o
Externí odkaz:
https://doaj.org/article/d1d3f3d5da0c489da7045c809d57a322
Recently, the self-supervised pre-training paradigm has shown great potential in leveraging large-scale unlabeled data to improve downstream task performance. However, increasing the scale of unlabeled pre-training data in real-world scenarios requir
Externí odkaz:
http://arxiv.org/abs/2212.05473
Autor:
Liao, Chengjing, Cao, Fangbo, Huang, Min, Chen, Jiana, Yang, Yuanzhu, Fu, Chenjian, Zhao, Xinhui, Wang, Weiqin, Zheng, Huabin
Publikováno v:
In Food Chemistry: X 30 December 2024 24
Autor:
Yang, Jingkang, Wang, Haoqi, Feng, Litong, Yan, Xiaopeng, Zheng, Huabin, Zhang, Wayne, Liu, Ziwei
Current out-of-distribution (OOD) detection benchmarks are commonly built by defining one dataset as in-distribution (ID) and all others as OOD. However, these benchmarks unfortunately introduce some unwanted and impractical goals, e.g., to perfectly
Externí odkaz:
http://arxiv.org/abs/2108.11941
Deep semi-supervised learning (SSL) has experienced significant attention in recent years, to leverage a huge amount of unlabeled data to improve the performance of deep learning with limited labeled data. Pseudo-labeling is a popular approach to exp
Externí odkaz:
http://arxiv.org/abs/2108.06070
Autor:
Ma, Liping, Zheng, Huabin, Ke, Xianliang, Gui, Rui, Yao, Zhongzi, Xiong, Jiasong, Chen, Quanjiao
Publikováno v:
In Virologica Sinica February 2024 39(1):56-70
Webly supervised learning becomes attractive recently for its efficiency in data expansion without expensive human labeling. However, adopting search queries or hashtags as web labels of images for training brings massive noise that degrades the perf
Externí odkaz:
http://arxiv.org/abs/2010.05864
Autor:
Yang, Jingkang, Feng, Litong, Chen, Weirong, Yan, Xiaopeng, Zheng, Huabin, Luo, Ping, Zhang, Wayne
This paper focuses on webly supervised learning (WSL), where datasets are built by crawling samples from the Internet and directly using search queries as web labels. Although WSL benefits from fast and low-cost data collection, noises in web labels
Externí odkaz:
http://arxiv.org/abs/2008.11894
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.