暗语
发表于 2025-3-23 11:38:35
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Obverse
发表于 2025-3-23 15:13:00
duce bandwidth consumption. While machine learning (ML) models can run on smaller computing devices at the edge, training ML models presents challenges for low-capacity devices. This paper aimed to evaluate the performance of Federated Learning (FL) - a distributed ML framework, when training a medi
中世纪
发表于 2025-3-23 20:12:01
Hu-Chen Liued client data sets to jointly construct a global model under the coordination of a central server. However, in practical applications, there is a high degree of data distribution skewness among clients, which causes the optimization direction of the client models to diverge, resulting in model bias
多骨
发表于 2025-3-23 23:47:22
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VEN
发表于 2025-3-24 02:51:46
Hu-Chen Liung of shared learning models while ensuring data privacy. However, existing FL still face numerous challenges in IoV. Firstly, the fast convergence with FL models is difficult to achieve due to the high mobility of vehicles and the non-independent identical distribution (Non-IID) among data collecte
迅速成长
发表于 2025-3-24 07:34:51
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FLAG
发表于 2025-3-24 12:18:22
Hu-Chen Liu large difference in the volume of stroke lesion areas and the great similarity between lesion areas and normal tissues, most of the existing methods for lesion segmentation cannot deal with these problems well. This paper proposes a novel network named MD-TransUNet for the segmentation of stroke le
表两个
发表于 2025-3-24 18:27:17
Hu-Chen Liu naturally represented as graphs, Graph Neural Networks (GNNs) have proven highly effective for learning graph representations of source code. Pooling, as an essential operation for GNN-based models, is limited in its ability to leverage the rich hierarchical information presented in tree-like graph
Adjourn
发表于 2025-3-24 22:42:43
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我怕被刺穿
发表于 2025-3-25 00:16:21
FMEA Using ITHWD Measure and Its Application to Blood Transfusione the performance of the traditional FMEA method. The new model can not only handle the uncertainty and diversity of FMEA team members’ risk assessments but also consider the subjective and objective weights of risk factors in the risk ranking process. Moreover, it has exact characteristic and can a