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Open Challenges and Opportunities in Federated Foundation Models Towards Biomedical Healthcare
This survey explores the transformative impact of foundation models (FMs) in artificial intelligence, focusing on their integration with federated learning (FL) for advancing biomedical research.
Cooperative Route Guidance and Flow Control for Mixed Road Networks Comprising Expressway and Arterial Network
Facing the congestion challenges of mixed road networks comprising expressways and arterial road networks, traditional control solutions fall short.
Adaptive Transfer Learning of Multi-View Time Series Classification
In this paper, we first proposed a general adaptive transfer learning framework for multi-view time series data, which shows strong ability in storing inter-view importance value in the process of knowledge transfer.
LEARN: Learned Experts' Assessment-based Reconstruction Network for Sparse-data CT
Compressive sensing (CS) has proved effective for tomographic reconstruction from sparsely collected data or under-sampled measurements, which are practically important for few-view CT, tomosynthesis, interior tomography, and so on.
Low-dose CT denoising with convolutional neural network
To reduce the potential radiation risk, low-dose CT has attracted much attention.
Low-Dose CT via Deep Neural Network
In order to reduce the potential radiation risk, low-dose CT has attracted more and more attention.
Medical Physics
