Researchers have developed a multi-view collaborative variational autoencoder that leverages knowledge distillation transfer learning to predict lncRNA associations in cervical ...
Researchers developed a machine learning framework using historical geolocated social media traces to detect and classify routine cross-border commuting flows ...
A focused review of 27 studies highlights the shift from traditional image processing to deep learning architectures for automated concrete ...
A new non-destructive method uses normalized RGB imaging and transfer learning to predict surface moisture at exposed earthen sites with ...
A systematic review of 62 studies reveals that deep learning models effectively monitor marine biodiversity across distinct aquatic mediums despite ...
A transfer learning framework adapting adult glioma models to paediatric FLAIR MRI enables fully automated F-DOPA PET segmentation and prognostic ...
A hybrid data-driven framework combining finite element simulations and transfer learning predicts fiber-reinforced soft actuator bending deformation with high precision.
Researchers developed a dual-branch artificial intelligence framework combining deep learning and radiomics to detect Helicobacter pylori infection from gastroscopy images.
Lobar classical radiomics from combined inspiratory and expiratory CT scans outperformed handcrafted measures in detecting chronic airflow limitation in a ...
An iterative deep learning framework accurately forecasts community disease surges three days ahead by analyzing coronavirus genetic material in municipal ...
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