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 ...

We develop a new edge detection algorithm, holistically-nested edge detection (HED), which performs image-to-image prediction by means of a deep learning model that leverages fully convolutional ...

Abstract: Low-dose computed tomography (LDCT) reduces radiation exposure but suffers from high noise, impacting image quality and diagnostic accuracy. Supervised learning has helped address this ...

Abstract: For infrared small-target detection, convolutional neural network (CNN)-based methods have demonstrated promising performance. However, due to the small size of the targets, existing ...

From The Matrix to tangled wizard wars, these trilogies buried great ideas under lore, retcons, and endless explanations.

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

Meta released Brain2Qwerty v2, an AI system that decodes brain activity into typed sentences using external MEG sensors ...

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

Chinese AI models have priced their APIs 5–10x lower than those of Anthropic and OpenAI. But is that sustainable? Chinese AI models are significantly underpricing their APIs compared to US ...

SummaryRFIC design is a complex “dark art” that limits progress in wireless technologies like 5G, autonomous vehicles, and ...

For example, AI applications to medical diagnosis should be regulated very differently from AI applications to self-driving cars. U.S. National Academies report on AI and the Future of Work, study ...

The key to more powerful plugins may be the graphics processor that you already have in your computer ...