Zobrazeno 1 - 10
of 24 562
pro vyhledávání: '"Semi-Supervised Learning"'
Publikováno v:
BMC Cardiovascular Disorders, Vol 24, Iss 1, Pp 1-19 (2024)
Abstract Background Late gadolinium enhancement cardiac magnetic resonance imaging (LGE-CMR) is a valuable cardiovascular imaging technique. Segmentation of cardiac chambers from LGE-CMR is a fundamental step in electrophysiological modeling and card
Externí odkaz:
https://doaj.org/article/b14d7d49d3304a7ebc5de8cffba0765e
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Deep learning-based defect detection methods have gained widespread application in industrial quality inspection. However, limitations such as insufficient sample sizes, low data utilization, and issues with accuracy and speed persist. This
Externí odkaz:
https://doaj.org/article/b8e67403a13c4c7c93894623831e6121
Autor:
Jun Ma, Xiaolong Zhu
Publikováno v:
AIMS Mathematics, Vol 9, Iss 9, Pp 25705-25731 (2024)
In this study, we introduced an innovative and robust semi-supervised learning strategy tailored for high-dimensional data categorization. This strategy encompasses several pivotal symmetry elements. To begin, we implemented a risk regularization fac
Externí odkaz:
https://doaj.org/article/1d8a99ff5c25494e823afbd414ec5e59
Publikováno v:
Digital Communications and Networks, Vol 10, Iss 4, Pp 1168-1177 (2024)
Hybrid precoding is considered as a promising low-cost technique for millimeter wave (mm-wave) massive Multi-Input Multi-Output (MIMO) systems. In this work, referring to the time-varying propagation circumstances, with semi-supervised Incremental Le
Externí odkaz:
https://doaj.org/article/597fe7225a5342e1959a0c9cc849770e
Autor:
Wenrui Guan, Xun Wang
Publikováno v:
Electronic Research Archive, Vol 32, Iss 7, Pp 4398-4415 (2024)
Graph Convolutional Networks (GCNs) demonstrate an excellent performance in node classification tasks by updating node representation via aggregating information from the neighbor nodes. Note that the complex interactions among all the nodes can prod
Externí odkaz:
https://doaj.org/article/869e66609f6d4f43bdc818635c160845
Publikováno v:
Geo-spatial Information Science, Pp 1-19 (2024)
Recent advancements in satellite remote sensing technology and computer vision have enabled rapid extraction of road networks from massive, Very High-Resolution (VHR) satellite imagery. However, current road extraction methods face the following limi
Externí odkaz:
https://doaj.org/article/d4538b27351d407885e29da57b1cae50
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 134, Iss , Pp 104160- (2024)
High-quality land-use/land-cover mapping with optical remote sensing images yet presents significant work. Even though fully convolutional semantic segmentation models have recently contributed to popular solutions, the lack of annotation data may le
Externí odkaz:
https://doaj.org/article/e5d3b87807984043a2f33b1de9008f7e
Autor:
Kauê T. N. Duarte, Abhijot S. Sidhu, Murilo C. Barros, David G. Gobbi, Cheryl R. McCreary, Feryal Saad, Richard Camicioli, Eric E. Smith, Mariana P. Bento, Richard Frayne
Publikováno v:
Frontiers in Computational Neuroscience, Vol 18 (2024)
IntroductionWhite matter hyperintensities (WMHs) are frequently observed on magnetic resonance (MR) images in older adults, commonly appearing as areas of high signal intensity on fluid-attenuated inversion recovery (FLAIR) MR scans. Elevated WMH vol
Externí odkaz:
https://doaj.org/article/a5b745a0d95a42878742d613f52fb0ac
Publikováno v:
Heliyon, Vol 10, Iss 20, Pp e39379- (2024)
Motivation: Distinguishing between pathogenic cancer-associated mutations and other somatic variants present in cell-free DNA (cfDNA) is one of the challenges in the field of liquid biopsy. This distinction is critical, since the misclassification of
Externí odkaz:
https://doaj.org/article/f140a5882a8d4aa38af180902f3a34f8
Publikováno v:
Frontiers in Artificial Intelligence, Vol 7 (2024)
IntroductionComputational models providing accurate estimates of their uncertainty are crucial for risk management associated with decision-making in healthcare contexts. This is especially true since many state-of-the-art systems are trained using t
Externí odkaz:
https://doaj.org/article/2ccf7ce269684cfdb6d56eb8e3a88616