In 540p-to-1080p comparisons, NSS improves stability and detail retention. It performs well in scenes with fast motion, ...

A new technical paper titled “Optimizing event-based neural networks on digital neuromorphic architecture: a comprehensive design space exploration” was published by imec, TU Delft and University of ...

Driven by the wave of the "new four modernizations" in the automotive industry, traditional distributed electronic and ...

Can a neural network be constructed entirely from DNA and yet learn in the same way as its silicon-based brethren? Recent ...

An MIT spinoff co-founded by robotics luminary Daniela Rus aims to build general-purpose AI systems powered by a relatively new type of AI model called a liquid neural network. The spinoff, aptly ...

The launch of the Hello Robotaxi marks a significant breakthrough for Hello Mobility in the field of autonomous driving. This model utilizes an end-to-end integrated architecture, meaning that the ...

What are convolutional neural networks in deep learning? Convolutional neural networks are used in computer vision tasks, which employ convolutional layers to extract features from input data.

Consider the multivariate nonparametric regression model. It is shown that estimators based on sparsely connected deep neural networks with ReLU activation function and properly chosen network ...

Article reviewed by Grace Lindsay, PhD from New York University. Scientists design ANNs to function like neurons. 6 They write lines of code in an algorithm such that there are nodes that each contain ...

Scientists at UCL, Google DeepMind and Intrinsic have developed a powerful new AI algorithm that enables large sets of ...