Endogenous intracellular allosteric modulators of GPCRs remain largely unexplored, with limited binding and phenotype data available. This gap arises from the lack of robust computational methods for ...

This paper aims to develop an advanced deep learning model that improves segmentation accuracy while maintaining computational efficiency, offering a solution to the limitations of existing methods.

In the Sahel region, the RegCM4-HadGEM2 model gave a good correlation. Using the Taylor diagram in the historical period, all CORDEX-CORE RCMs had a strong relationship with temperature.

Abstract: Developing deep learning ... with a dual encoder-decoder. The proposed novel deep quasi-recurrent self-attention architecture evokes parameter reuse capability that offers consistency in ...

Since there is no story-based dataset to draw from, a standard deep learning strategy of merely learning this task from data is not feasible. Instead, Phenaki uses a model that was designed ...

A combination of data-driven model reduction strategies and machine learning (deep-neural networks–DNN ... The residual convolutional block used in the decoder has the same structure as the used on ...

Glioma is the most common primary central nervous system tumor, accounting for about half of all intracranial primary tumors. As a non-invasive examination method, MRI has an extremely important ...