Zobrazeno 1 - 10
of 207
pro vyhledávání: '"Shuaiqi Liu"'
Publikováno v:
CAAI Transactions on Intelligence Technology, Vol 9, Iss 4, Pp 879-893 (2024)
Abstract Diagnosing individuals with autism spectrum disorder (ASD) accurately faces great challenges in clinical practice, primarily due to the data's high heterogeneity and limited sample size. To tackle this issue, the authors constructed a deep g
Externí odkaz:
https://doaj.org/article/3234826ffa6549c68579d92c563b0c6c
Autor:
Shiheng Li, Senyang Li, Shuaiqi Liu, Shunli Lu, Jing Li, Shuqi Cheng, Sumei Zhang, Shucheng Huang, Junqiang Li, Fuchun Jian
Publikováno v:
AMB Express, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract Coccidia of the genus Eimeria are important pathogens that cause coccidiosis in livestock and poultry. Due to the expansion of intensive farming, coccidiosis has become more difficult to control. In addition, the continued use of anti-coccid
Externí odkaz:
https://doaj.org/article/ff4ad9d29a814445968c87d82b4d6988
Autor:
Shuaiqi Liu, Qingxiao Zheng
Publikováno v:
Blockchain: Research and Applications, Vol 5, Iss 2, Pp 100192- (2024)
To address the challenges of low credibility, difficult data sharing, and regulatory supervision issues involving electronic evidence storage in the judicial preservation process, this paper proposes a blockchain-based judicial evidence preservation
Externí odkaz:
https://doaj.org/article/575fc3a5cbba4903af1490f76d350388
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 428-433 (2024)
Goal: The purpose of this paper is to recognize autism spectrum disorders (ASD) using graph attention network. Methods: we propose a node features graph attention network (NF-GAT) for learning functional connectivity (FC) features to achieve ASD diag
Externí odkaz:
https://doaj.org/article/42110df3d4ad4889b45d401d4b37aa43
Publikováno v:
Mathematical Biosciences and Engineering, Vol 20, Iss 12, Pp 21537-21562 (2023)
In recent years, with the continuous development of artificial intelligence and brain-computer interfaces, emotion recognition based on electroencephalogram (EEG) signals has become a prosperous research direction. Due to saliency in brain cognition,
Externí odkaz:
https://doaj.org/article/35f52e5c3d4a4daab5ba9da096d97a60
Autor:
Shuaiqi Liu, Yundong Zhang, Huanzhi Zhang, Jiaming Zhang, Maoxin Qiu, Guang Li, Fengshan Ma, Jie Guo
Publikováno v:
Frontiers in Earth Science, Vol 11 (2023)
Hydraulic fracturing is an essential technique for reservoir stimulation in the process of deep energy exploitation. Granite is composed of different rock-forming minerals and exhibits obvious heterogeneity at the mesoscale, which affects the strengt
Externí odkaz:
https://doaj.org/article/fabcaff18e174d648deadf208b1ff826
Autor:
Zhipeng Cao, Liangcun Jiang, Peng Yue, Jianya Gong, Xiangyun Hu, Shuaiqi Liu, Haofeng Tan, Chang Liu, Boyi Shangguan, Dayu Yu
Publikováno v:
Geo-spatial Information Science, Pp 1-20 (2023)
ABSTRACTArtificial Intelligence (AI) Machine Learning (ML) technologies, particularly Deep Learning (DL), have demonstrated significant potential in the interpretation of Remote Sensing (RS) imagery, covering tasks such as scene classification, objec
Externí odkaz:
https://doaj.org/article/35b755753428416f8762e33772c09a68
Publikováno v:
Minerals, Vol 14, Iss 5, p 449 (2024)
The discovery of eclogite outcrops in the East Kunlun Orogen Belt (EKOB) has confirmed the existence of an Early Paleozoic HP-UHP metamorphic belt. However, the protoliths and metamorphic histories of widespread metabasites remain poorly constrained.
Externí odkaz:
https://doaj.org/article/5dc49e0e247747ec9c0f27994fc9973d
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 35, Iss 9, Pp 101751- (2023)
For multi-focus image fusion, the existing deep learning based methods cannot effectively learn the texture features and semantic information of the source image to generate high-quality fused images. Thus, we develop a new adaptive feature concatena
Externí odkaz:
https://doaj.org/article/afe96816ce534ccf9290268b804209ba
Publikováno v:
Tehnički Vjesnik, Vol 30, Iss 2, Pp 426-433 (2023)
Credit customer subdivisions and borrower characteristics are essential tools for banks and lending companies to evaluate credit risk and make profits. This study proposes a Multi-Level Default Risk Rating (MLDRR) strategy based on a heterogeneous en
Externí odkaz:
https://doaj.org/article/de348aa36e89499abadb2ff5643c0555