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Found 8 papers, 1 papers with code
A Multi-Scale Spatial Transformer U-Net for Simultaneously Automatic Reorientation and Segmentation of 3D Nuclear Cardiac Images
Accurate reorientation and segmentation of the left ventricular (LV) is essential for the quantitative analysis of myocardial perfusion imaging (MPI), in which one critical step is to reorient the reconstructed transaxial nuclear cardiac images into standard short-axis slices for subsequent image processing.
Deep learning-based flow disaggregation for short-term hydropower plant operations
In this study, we propose a deep learning-based time series disaggregation model to derive hourly inflow data from daily inflow data for short-term hydropower plant operations.
Dynamic Grouping for Climate Change Negotiation: Facilitating Cooperation and Balancing Interests through Effective Strategies
We demonstrate our negotiation model within the RICE-N framework, illustrating a promising approach for facilitating international cooperation on climate change mitigation.
Dynamic Grouping for Climate Change Negotiation: Facilitating Cooperation and Balancing Interests through Effective Strategies
The current framework for climate change negotiation models presents several limitations that warrant further research and development.
DPA-1: Pretraining of Attention-based Deep Potential Model for Molecular Simulation
Machine learning assisted modeling of the inter-atomic potential energy surface (PES) is revolutionizing the field of molecular simulation.
Exploiting Capacity of Sewer System Using Unsupervised Learning Algorithms Combined with Dimensionality Reduction
Exploiting capacity of sewer system using decentralized control is a cost effective mean of minimizing the overflow.
Deep Learning for Real Time Crime Forecasting
Experiments over a half year period in Los Angeles reveal highly accurate predictive power of our models.
Principled Graph Matching Algorithms for Integrating Multiple Data Sources
In the most common case of matching two sources, it is often desirable for the final matching to be one-to-one (a record may be matched with at most one other); members of the database and statistical record linkage communities accomplish such matchings in the final stage by weighted bipartite graph matching on similarity scores.
