Abstract: Convolutional neural networks (CNNs) have recently led to incredible breakthroughs on a variety of pattern recognition problems. Banks of finite-impulse response filters are learned on a ...

Abstract: Most existing traditional and deep learning (DL)-based methods used for random noise attenuation or reconstruction of seismic data typically only process 2-D data. Very few methods are able ...

This GitHub Repository was produced to share material relevant to the Journal paper Automatic crack classification and segmentation on masonry surfaces using convolutional neural networks and transfer ...

Recently, in a lecture room at the Daegu Startup Hub in Dong-gu, Daegu, Kim Soo-pil, a senior researcher at the Daegu ...

This repo contains an example implementation of the Simple Graph Convolution (SGC) model, described in the ICML2019 paper Simplifying Graph Convolutional Networks. SGC removes the nonlinearities and ...

In 1989, a computer scientist tackled the messy challenge of reading handwritten zip codes for the US Post Office. This ...

A patent-pending innovation created and validated in Purdue University's College of Engineering could strengthen ...

By Pietro Antonio Ciclese, Senior Technical Marketing Engineer, Ambarella The workloads that generate the most commercial ...

A patent-pending innovation created and validated in Purdue University’s College of Engineering could strengthen ...

From detecting pancreatic cancer three years early to recognising 18 tumour types from a handful of tissue slides, AI is transforming medicine. Here is a comprehensive guide to the breakthroughs, the ...

AMD's new FSR 4.1 INT8 upscaler gives RDNA 3 GPUs a massive image quality upgrade. We examine visual quality, performance, ...