Abstract: In this paper, we propose a novel human crowd detection method that uses deep convolutional neural networks for drone flight safety purposes. The first contribution of this paper is to ...

The IBS-Yonsei research team introduces a novel Lp-Convolution method at ICLR 2025. A team of researchers from the (IBS), ...

Get Instant Summarized Text (Gist) A self-attention neural network model enables rapid and accurate prediction of radiation shielding designs for space reactors, achieving less than 3% deviation ...

OpenAI is working on its own X-like social network, according to multiple sources familiar with the matter. While the project is still in early stages, we’re told there’s an internal prototype ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...

Networks programmed directly into computer chip hardware can identify images faster, and use much less energy, than the traditional neural networks that underpin most modern AI systems.

In other words, games that are no longer rendered by a traditional 3D pipeline, but fully rendered by neural networks. The technology could arrive with Blackwell, a new graphics architecture that ...

He later published influential papers on backpropagation (the learning process used in modern machine learning systems) and convolutional neural networks (the main type of neural network used ...

Convolutional neural networks (CNNs), with their exceptional image recognition capabilities, have performed outstandingly in the field of AI and notably within platforms like ChatGPT. Recently, a team ...

That's generally not true in the field of generative AI, where the non-interpretable neural networks underlying these models make it hard for even experts to figure out precisely why they often ...