Zobrazeno 1 - 10
of 820
pro vyhledávání: '"ZHOU Dawei"'
Publikováno v:
Meikuang Anquan, Vol 54, Iss 4, Pp 156-162 (2023)
In view of the problems existing in traditional shaft safety monitoring methods such as low efficiency(need monitoring after production stop), less data and large error, a method of monitoring shaft tilt deformation with laser SLAM (Simultaneous Loca
Externí odkaz:
https://doaj.org/article/896eb883191d45479f297898c4b92444
Autor:
Beigi, Mohammad, Wang, Sijia, Shen, Ying, Lin, Zihao, Kulkarni, Adithya, He, Jianfeng, Chen, Feng, Jin, Ming, Cho, Jin-Hee, Zhou, Dawei, Lu, Chang-Tien, Huang, Lifu
In recent years, Large Language Models (LLMs) have become fundamental to a broad spectrum of artificial intelligence applications. As the use of LLMs expands, precisely estimating the uncertainty in their predictions has become crucial. Current metho
Externí odkaz:
http://arxiv.org/abs/2410.20199
Continual Learning (CL) aims to learn in non-stationary scenarios, progressively acquiring and maintaining knowledge from sequential tasks. Recent Prompt-based Continual Learning (PCL) has achieved remarkable performance with Pre-Trained Models (PTMs
Externí odkaz:
http://arxiv.org/abs/2409.18860
Autor:
Wang Rui, Wu Shuang, Wu Kan, Huang Shiqiao, Wu Ruijie, Liu Bo, Lin Min, Li Liang, Zhou Dawei, Diao Xinpeng
Publikováno v:
IEEE Access, Vol 9, Pp 64880-64894 (2021)
With the exploitation of mineral resources, pollution of the ecological environment in mines has garnered public attention. Particularly,erosion of the surrounding ecological environment re-sulting from heavy metals in tailings pond could be highly c
Externí odkaz:
https://doaj.org/article/bfbadcbd3709440581b8a37c90a42069
Many real-world graphs frequently present challenges for graph learning due to the presence of both heterophily and heterogeneity. However, existing benchmarks for graph learning often focus on heterogeneous graphs with homophily or homogeneous graph
Externí odkaz:
http://arxiv.org/abs/2407.10916
Autor:
Hoggenmuller, Marius, Tomitsch, Martin, Parker, Callum, Nguyen, Trung Thanh, Zhou, Dawei, Worrall, Stewart, Nebot, Eduardo
The advent of cyber-physical systems, such as robots and autonomous vehicles (AVs), brings new opportunities and challenges for the domain of interaction design. Though there is consensus about the value of human-centred development, there is a lack
Externí odkaz:
http://arxiv.org/abs/2406.08733
Although most graph neural networks (GNNs) can operate on graphs of any size, their classification performance often declines on graphs larger than those encountered during training. Existing methods insufficiently address the removal of size informa
Externí odkaz:
http://arxiv.org/abs/2406.04601
Adversarial training (AT) trains models using adversarial examples (AEs), which are natural images modified with specific perturbations to mislead the model. These perturbations are constrained by a predefined perturbation budget $\epsilon$ and are e
Externí odkaz:
http://arxiv.org/abs/2406.00685
Publikováno v:
IEEE Access, Vol 8, Pp 16372-16386 (2020)
This study mainly presents the method for monitoring the surface dynamic subsidence basin (SDSB) caused by underground coal mining and obtaining parameters of mining subsidence (PMS) in the short term by using an unmanned aerial vehicle (UAV) Photogr
Externí odkaz:
https://doaj.org/article/14479d134c664a0a979f4beabe69c32a
Spatiotemporal time series are usually collected via monitoring sensors placed at different locations, which usually contain missing values due to various failures, such as mechanical damages and Internet outages. Imputing the missing values is cruci
Externí odkaz:
http://arxiv.org/abs/2403.11960