A novel Graph Convolutional Pre-trained Contrastive Cross-Fusion (GPC-CF) framework, which integrates EEG and fMRI data within a pre-training and fine-tuning model to establish a powerful paradigm for multimodal brain signal fusion.
Rui-Zhe Zhong, Hai-Sheng Li, Min Zuo et al.· IEEE Access· 0 citations
A physics-enhanced bidirectional multi-order graph fusion network for interpretable bearing RUL prediction and a physics-enhanced dynamic loss function is developed to help the network learn effective and reliable degradation representations.
Haoxuan Zhang, Ding-Hao Yang, Kang-Ning Zhang et al.· 0 citations
Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) provide complementary information about brain function, and have shown significant promise in detecting functional abnormalities in various brain disorders. However, the distinct signal characteristics and disparate representational spaces of...
Fruit and vegetable supply chains generate heterogeneous data across production, storage, logistics, and sales, creating challenges for trusted data sharing, privacy protection, and real-time traceability across distributed supply-chain information systems. Conventional single-chain blockchains suffer from limited scal...
Weiqiang Chen, Zhi-Yao Zhao, Hai-Sheng Li et al.· Computers· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
