Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...

Recently, a research team led by Prof. GAO Xiaoming from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, developed an intelligent neural network algorithm that effectively ...

FLAMeS, a new convolutional neural network, enhances MS lesion segmentation accuracy using only T2-weighted FLAIR images, ...

In a study published in Frontiers in Science, scientists from Purdue University and the Georgia Institute of Technology ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

Research reveals why AI systems can't become conscious—and what radically different computing substrates would be needed to ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, innovatively launches a quantum-enhanced deep convolutional neural network image 3D reconstruction ...

A new fingerprint matching algorithm developed by Precise Biometrics delivers significantly higher accuracy, along with stronger security and easier use.