Learn what CNN is in deep learning, how they work, and why they power modern image recognition AI and computer vision programs.

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 ...

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

Image courtesy by QUE.com Artificial Intelligence (AI) has become a buzzword in today’s tech-driven world, promising new ...

Researchers from Zhejiang Lab have proposed a novel spatiotemporal mode multiplexing technology, coupling pulsed orbital angular momentum (OAM) beams with diffractive deep neural networks (D2NN) and ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, structureless data. Yet when trained on datasets with structure, they learn the ...

The simplified approach makes it easier to see how neural networks produce the outputs they do. A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher.

Machine learning techniques that make use of tensor networks could manipulate data more efficiently and help open the black ...

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the tail end ...