Zobrazeno 1 - 10
of 857
pro vyhledávání: '"Liu Chengliang"'
Autor:
Zhang Hong'ou, George C S Lin, He Shenjing, Huang Gengzhi, Ye Yuyao, Liu Chengliang, Luo Yan, Yang Yu, Liu Helin, Pan Fenghua, Zhu Shengjun, Li Yurui, Hu Zhiding, Yang Zhenshan, Zhou Xia, Wu Qitao, Yang Ren, Sun Wei, Ma Haitao, Liang Yutian, Wang Fenglong, An Ning, Yuan Zhenjie, Guo Yan, Xi Guangliang, Hu Xiaohui, Lin Qiang, Liu Yi, Huang Jie
Publikováno v:
Redai dili, Vol 43, Iss 8, Pp 1453-1478 (2023)
Owing to the development issues of the Guangdong-Hong Kong-Macao Greater Bay Area in the new domestic and international situation, the content, challenges, and paths of innovation and development of the Greater Bay Area are explored from multiple dim
Externí odkaz:
https://doaj.org/article/b89f535171b941c18f29e0e5fb1025fb
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-6 (2022)
Abstract To ascertain the prevalence of contralateral patent processus vaginalis (CPPV) in life and the significance of the prevalence trends for treatment. We performed a retrospective review of all inguinal hernias (IHs) that underwent repair in ou
Externí odkaz:
https://doaj.org/article/04cb6de035d945948be79f0098180d44
Publikováno v:
Open Geosciences, Vol 13, Iss 1, Pp 245-261 (2021)
Open Geospatial Consortium (OGC) Web Services (OWS) are highly significant for geospatial data sharing and widely used in many scientific fields. However, those services are hard to find and utilize effectively. Focusing on addressing the big challen
Externí odkaz:
https://doaj.org/article/5d450eb8c1634fd18f5268b1de96f8b3
Publikováno v:
智慧农业, Vol 2, Iss 4, Pp 17-40 (2020)
Vegetable and fruit harvesting is the most difficult production process to achieve mechanized operations. High-efficiency and low-loss picking is also a worldwide problem in the field of agricultural robot research and development, resulting in few p
Externí odkaz:
https://doaj.org/article/da0d0404315f42c5a712b47f1495e006
Publikováno v:
智慧农业, Vol 2, Iss 4, Pp 149-164 (2020)
The orchard is usually with a wide area, complex terrain, many trenches, overgrown weeds, high soil moisture and relatively loose soil, which greatly restrict the mechanization and intelligence, and put forward higher standards and requirements for t
Externí odkaz:
https://doaj.org/article/c04c5c96d7b944d0930d2f75d700e029
Multi-view learning has become a popular research topic in recent years, but research on the cross-application of classic multi-label classification and multi-view learning is still in its early stages. In this paper, we focus on the complex yet high
Externí odkaz:
http://arxiv.org/abs/2404.17340
Autor:
Chen, Zhaorun, Zhao, Zhuokai, He, Tairan, Chen, Binhao, Zhao, Xuhao, Gong, Liang, Liu, Chengliang
Ensuring safety in Reinforcement Learning (RL), typically framed as a Constrained Markov Decision Process (CMDP), is crucial for real-world exploration applications. Current approaches in handling CMDP struggle to balance optimality and feasibility,
Externí odkaz:
http://arxiv.org/abs/2310.03379
Autor:
Liu, Chengliang, Huang, Binhua, Liu, Yiwen, Su, Yuanzhe, Mai, Ke, Zhang, Yupo, Yi, Zhengkun, Wu, Xinyu
In this paper, we investigate the effectiveness of contrastive learning methods for predicting grasp outcomes in an unsupervised manner. By utilizing a publicly available dataset, we demonstrate that contrastive learning methods perform well on the t
Externí odkaz:
http://arxiv.org/abs/2306.14437
Incomplete multi-view clustering is a hot and emerging topic. It is well known that unavoidable data incompleteness greatly weakens the effective information of multi-view data. To date, existing incomplete multi-view clustering methods usually bypas
Externí odkaz:
http://arxiv.org/abs/2304.00429
As a cross-topic of multi-view learning and multi-label classification, multi-view multi-label classification has gradually gained traction in recent years. The application of multi-view contrastive learning has further facilitated this process, howe
Externí odkaz:
http://arxiv.org/abs/2303.17117