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

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

“Over the past decade, deep-learning-based representations have demonstrated remarkable performance in academia and industry. The learning capability of convolutional neural networks (CNNs) originates ...

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

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

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.

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 ...

The AI revolution continuously requires new tools and methods to take full advantage of its promise, especially when dealing with imaging data beyond visible wavelengths of the electromagnetic ...

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 ...