上釉彩 发表于 2025-3-25 06:46:28
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Joerg Deigmoeller,Pavel Smirnov,Julian Eggert,Chao Wang,Johane TakeuchiCIS 发表于 2025-3-25 13:32:18
Davide Varagnolo,Dora Melo,Irene Pimenta Rodrigues,Rui Rodrigues,Paula Couto原谅 发表于 2025-3-25 18:07:24
Knowledge Discovery, Knowledge Engineering and Knowledge Management14th International JAudiometry 发表于 2025-3-25 23:49:46
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Degree Centrality Definition, and Its Computation for Homogeneous Multilayer Networks Using Heurististics-based algorithms for computing degree centrality on MLNs . using the decoupling-based approach which has been shown to be efficient as well as structure and semantics preserving. We compare the accuracy and precision of our algorithms with Boolean OR-aggregated graphs of Homogeneous MLNs as grRODE 发表于 2025-3-26 04:31:06
A Dual-Stage Noise Training Scheme for Breast Ultrasound Image Classification used backbone CNN architectures in the medical image classification field: AlexNet, ResNet-18, ResNet-50, and VGG16. They are fine-tuned on carefully constructed noisy datasets, and the test results suggest that they all acquire remarkable noise resistance, and this immunity is almost invariant to不可磨灭 发表于 2025-3-26 11:54:25
A General-Purpose Multi-stage Multi-group Machine Learning Framework for Knowledge Discovery and Decmedical problems that involve poorly separated data and imbalanced groups in which traditional classifiers yield low prediction accuracy: (a) multi-site treatment outcome prediction for best practice discovery in cardiovascular disease; and (b) diabetes; (c) early disease diagnosis in predicting subepicardium 发表于 2025-3-26 13:02:10
Comparative Assessment of Deep End-To-End, Deep Hybrid and Deep Ensemble Learning Architectures for d voting over a hematoxylin and eosin (H&E)-stained pathological images. The experiments were conducted using the public BreakHis dataset, 5-fold cross validation method, four metrics of performances, the Scott Knott statistical test and the Borda Count voting method. The results showed that the dee屈尊 发表于 2025-3-26 17:19:11
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