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

Understanding the brain's functional architecture is a fundamental challenge in neuroscience. The connections between neurons ultimately dictate how information is processed, transmitted, stored, and ...

“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 ...

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 ...

Fully convolutional networks (FCNs) are a type of neural network architecture commonly used in computer vision tasks such as image segmentation, object detection and image classification.

Recently, Anhui Zhongji Star Electronic Technology Co., Ltd. submitted a patent application titled "Dynamic Control Method ...

The neural network architecture they developed, Netcast, involves storing weights in a central server that is connected to a novel piece of hardware called a smart transceiver.

Artificial Neural Network Architecture Example For image analysis purposes, an image’s pixels are converted into grayscale values and each pixel becomes a numerical input that enters the neural ...