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Found 10 papers, 1 papers with code
Flexible Multi-Generator Model with Fused Spatiotemporal Graph for Trajectory Prediction
Trajectory prediction plays a vital role in automotive radar systems, facilitating precise tracking and decision-making in autonomous driving.
A Multimodal Learning Framework for Comprehensive 3D Mineral Prospectivity Modeling with Jointly Learned Structure-Fluid Relationships
This study presents a novel multimodal fusion model for three-dimensional mineral prospectivity mapping (3D MPM), effectively integrating structural and fluid information through a deep network architecture.
A Transformer-based Deep Learning Algorithm to Auto-record Undocumented Clinical One-Lung Ventilation Events
We hypothesized that available intraoperative mechanical ventilation and physiological time-series data combined with other clinical events could be used to accurately predict missing start and end times of OLV.
Learning 3D Mineral Prospectivity from 3D Geological Models Using Convolutional Neural Networks: Application to a Structure-controlled Hydrothermal Gold Deposit
The three-dimensional (3D) geological models are the typical and key data source in the 3D mineral prospecitivity modeling.
End-to-End Transmission Analysis of Simultaneous Wireless Information and Power Transfer using Resonant Beam
Integrating the wireless power transfer (WPT) technology into the wireless communication system has been important for operational cost saving and power-hungry problem solving of electronic devices.
Retro-Reflective Beam Communications with Spatially Separated Laser Resonator
Optical wireless communications (OWC) utilizing infrared or visible light as the carrier attracts great attention in 6G research.
Federated machine learning with Anonymous Random Hybridization (FeARH) on medical records
Sometimes electrical medical records are restricted and difficult to centralize for machine learning, which could only be trained in distributed manner that involved many institutions in the process.
LoAdaBoost: loss-based AdaBoost federated machine learning with reduced computational complexity on IID and non-IID intensive care data
One challenge in applying federated machine learning is the possibly different distributions of data from diverse sources.
Mobile Power Network for Ultimate Mobility without Battery Life Anxiety
We propose here the next generation of power delivery network -- mobile power network (MPN) for wireless power transfer within a mobile range from several meters to tens of meters.
PCM and APCM Revisited: An Uncertainty Perspective
Experiments show that parameters $\sigma_v$ and $\alpha$ make the clustering process more easy to control, and main features of PCM and APCM are unified in this new clustering framework (UPCM).
