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Joint Sparse Representations and Coupled Dictionary Learning in Multi-Source Heterogeneous Image Pseudo-color Fusion
Considering that Coupled Dictionary Learning (CDL) method can obtain a reasonable linear mathematical relationship between resource images, we propose a novel CDL-based Synthetic Aperture Radar (SAR) and multispectral pseudo-color fusion method.
Hierarchical Graph Pooling is an Effective Citywide Traffic Condition Prediction Model
Accurate traffic conditions prediction provides a solid foundation for vehicle-environment coordination and traffic control tasks.
Transfer Learning and Vision Transformer based State-of-Health prediction of Lithium-Ion Batteries
At the same time, transfer learning (TL) is introduced, and the prediction model based on source task battery training is further fine-tuned according to the early cycle data of the target task battery to provide an accurate prediction.
Spatial-Temporal Feature Extraction and Evaluation Network for Citywide Traffic Condition Prediction
The spatial and temporal features in traffic data are extracted by multi-graph graph convolution and attention mechanism, and different combinations of spatial and temporal features are generated.
A Transferable Intersection Reconstruction Network for Traffic Speed Prediction
Then, the spatial information is subdivided into intersection information and sequence information of traffic flow direction, and spatiotemporal features are obtained through various models.
