A Convolutional Neural Network (CNN ... This design principle enables the network to maintain consistent feature detection capabilities across the entire input image while minimizing memory ...

We now have a partial network diagram of ... they're being stubborn; convolutional neural nets simply aren't built to show their work. They consist of an input layer, one or more hidden layers ...

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 a two-streams ...

MLCommons' AI training tests show that the more chips you have, the more critical the network that's between them.

"Linear and Deformable Image Registration with 3D Convolutional Neural Networks", 2018. For a quick introduction to image registration and summary of the paper check out this presentation. Note: This ...

Levels of supply and demand for varying prices can be plotted on a graph as curves, and the intersection of these curves marks the equilibrium or market-clearing price at which demand equals ...

To address this gap, we propose a novel point-based multiscale spatial Convolution-Swin Transformer network (Point-SCT). Point-SCT combines convolutional local geometric detail capture with global ...