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 work presents a framework based on adaptive graph convolution network (AGCN) to process both 2D and 3D facial landmarks extracted from the input RGB image. The network has ... for performance ...

Here’s something fun. Our hacker [Willow Cunningham] has sent us a copy of their homework. This is their final project for the “ECE 574: Cluster Computing” course at the University of Maine ...

Image processing is manipulation of an image that has been digitised and uploaded into a computer. Software programs modify the image to make it more useful, and can for example be used to enable ...

To address these issues, we propose a novel framework, pyramid network (PYN), that leverages multiscale feature fusion and a novel multihedron dynamic graph convolutional network (MHDGCN). PYN ...

Optimized for Entry-Level DMS With Industry’s Lowest Power Consumption and Board Space for Processing Eye Gaze and Eye Tracking Algorithms; ASIC and Image Sensor, Combined, Consume Less Than 1 Watt ...

Motivated by these challenges, we propose an innovative prediction algorithm named dual-channel graph and Hypergraph Convolutional Network (DCGHCN) to discover microbes underlying disease traits.

torch==1.9.0 tqdm==4.61.2 torch_scatter==2.0.7 torch_geometric==2.0.2 torch_sparse==0.6.10 pandas==1.1.5 matplotlib==3.3.4 scipy==1.5.4 numpy==1.16.2 loguru==0.5.3 scikit-learn==1.0.1 ...