Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Peishun Liu"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract This paper proposes an innovative global solution which is a pioneering work applying automated machine learning algorithms to remarkable precision sparse underwater direction-of-arrival (DOA) estimation that views the subaquatic sparse-samp
Externí odkaz:
https://doaj.org/article/f9429d6f32b54cf5aa4ebc5109500b23
Publikováno v:
Symmetry, Vol 16, Iss 10, p 1342 (2024)
The rich information and complex background of industrial images make it a challenging task to improve the high compression rate of images. Current learning-based image compression methods mostly use customized convolutional neural networks (CNNs), w
Externí odkaz:
https://doaj.org/article/5c5f10a292bf4be7ae4a479a2cd8b2f0
Autor:
Li Yan, Gaozhou Wang, Hongxin Feng, Peishun Liu, Haojie Gao, Wenbin Zhang, Hailin Hu, Fading Pan
Publikováno v:
Heliyon, Vol 10, Iss 12, Pp e32404- (2024)
To ensure secure and flexible data sharing in cloud storage, attribute-based encryption (ABE) is introduced to meet the requirements of fine-grained access control and secure one-to-many data sharing. However, the computational burden imposed by attr
Externí odkaz:
https://doaj.org/article/bb6907099454430794f39070d992b519
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-2 (2024)
Externí odkaz:
https://doaj.org/article/5710c645488d46ffbea9180f4a36dfc3
Publikováno v:
Applied Sciences, Vol 14, Iss 2, p 774 (2024)
With the rapid development of deep learning, researchers are actively exploring its applications in the field of industrial anomaly detection. Deep learning methods differ significantly from traditional mathematical modeling approaches, eliminating t
Externí odkaz:
https://doaj.org/article/000f2ab3650448bbb19635964ec7f2eb
Publikováno v:
Applied Sciences, Vol 13, Iss 21, p 11707 (2023)
Due to the lack of a specific design for scenarios such as scale change, illumination difference, and occlusion, current person re-identification methods are difficult to put into practice. A Multi-Branch Feature Fusion Network (MFFNet) is proposed,
Externí odkaz:
https://doaj.org/article/b5425127d4934cedbed0cf83b4f51fe5
Publikováno v:
Applied Sciences, Vol 13, Iss 5, p 3288 (2023)
As the most widely used storage device today, hard disks are efficient and convenient, but the damage incurred in the event of a failure can be very significant. Therefore, early warnings before hard disk failure, allowing the stored content to be ba
Externí odkaz:
https://doaj.org/article/74cf9080d174400b9b317a4f648f9129
Publikováno v:
网络与信息安全学报, Vol 5, Pp 105-118 (2019)
The system log reflects the running status of the system and records the activity information of specific events in the system.Therefore,the rapid and accurate detection of the system abnormal log is important to the security and stability of the sys
Externí odkaz:
https://doaj.org/article/8e959a20ea094a8db80d8e99459fba8b
Autor:
Peishun Liu, Bing Tian, Xiaobao Liu, Shijing Gu, Li Yan, Leon Bullock, Chao Ma, Yin Liu, Wenbin Zhang
Publikováno v:
Applied Sciences, Vol 12, Iss 14, p 6993 (2022)
A knowledge graph can structure heterogeneous knowledge in the field of power faults, construct the correlation between different pieces of knowledge, and solve the diversification, complexity, and island of fault data. There are many kinds of entiti
Externí odkaz:
https://doaj.org/article/f2f841fc6f2046cba7a37287bf4820fe
Publikováno v:
Applied Sciences, Vol 12, Iss 2, p 632 (2022)
Early risk prediction of diabetes could help doctors and patients to pay attention to the disease and intervene as soon as possible, which can effectively reduce the risk of complications. In this paper, a GA-stacking ensemble learning model is propo
Externí odkaz:
https://doaj.org/article/8cdd7d8412a0404f9fedc9c5e119a152