Abstract: Graph Convolution Networks (GCNs) have achieved remarkable success in representation of structured graph data. As we know that traditional GCNs are generally defined on the fixed first-order ...

In the Uniad model, we use the ResNet101 architecture as the img_backbone module. This model utilizes the ModulatedDeformConv2dPack class from the mmcv package, which internally relies on the ...

Introduction: This work presents a prototype electromagnetic actuation deformable mirror (DM) assembly with stress-resilient face sheet design. Methods: The DM face sheet design includes slender ...

In the generative adversarial network, I added 2-3 layers of deformable convolution, resulting in a large graphics card footprint. We did network training on the A800, which was not possible due to ...

ABSTRACT: This research investigates deep learning-based approach for defect detection in the steel production using Severstal steel dataset. The developed system integrates DenseNet121 for ...