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Found 6 papers, 2 papers with code
Multi-View Variational Autoencoder for Missing Value Imputation in Untargeted Metabolomics
By learning the latent representations of both omics data, our method can effectively impute missing metabolomics values based on genomic information.
Physics Inspired Hybrid Attention for SAR Target Recognition
There has been a recent emphasis on integrating physical models and deep neural networks (DNNs) for SAR target recognition, to improve performance and achieve a higher level of physical interpretability.
Leveraging Graph-based Cross-modal Information Fusion for Neural Sign Language Translation
Therefore, we propose to introduce additional word-level semantic knowledge of sign language linguistics to assist in improving current end-to-end neural SLT models.
Graph Neural Network and Superpixel Based Brain Tissue Segmentation (Corrected Version)
Convolutional neural networks (CNNs) are usually used as a backbone to design methods in biomedical image segmentation.
Plasticity Neural Network Based on Astrocytic effects at Critical Period, Synaptic Competition and Strength Rebalance by Current and Mnemonic Brain Plasticity and Synapse Formation
The relatively good and inferior gradient information stored in memory engram cells in synapse formation of retrograde circuit like the folds in brain [16].
A novel centroid update approach for clustering-based superpixel methods and superpixel-based edge detection
Then according to the statistical features of noise, we propose a novel centroid update approach to enhance the robustness of clustering-based superpixel methods.
