Adaptive method helps light-based quantum processors act more like neural networks

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...
PR Newswire APAC

MicroCloud Hologram Inc. Releases Next-Generation Quantum Convolutional Neural Network Multi-Class Classification Technology, Driving Quantum Machine Learning Towards ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, has launched a groundbreaking technological achievement—a multi-class classification method based on ...
optics.org

Rome-led group progresses toward practical photonic quantum neural networks

Photons are fast, stable, and easy to manipulate on chips, making photonic systems a promising platform for QCNNs. However, photonic circuits typically behave linearly, limiting the flexible ...
DatacenterDynamics

Brain-inspired architecture could cut compute power needed to train AI, researchers claim

A new approach to designing AI based on biologically inspired architecture could cut the number of data centers needed to run ...
TMCnet

WiMi Studies Hybrid Quantum-Classical Learning Architecture for Multi-Class Image Classification

In this architecture, the training process adopts a joint optimization mechanism based on classical cross-entropy loss. WiMi treats the measurement probability distribution output by the quantum ...
Embedded

Understanding convolutional neural networks

The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...
Visual Studio Magazine

Convolutional Neural Networks for MNIST Data Using PyTorch

Dr. James McCaffrey of Microsoft Research details the "Hello World" of image classification: a convolutional neural network (CNN) applied to the MNIST digits dataset. The "Hello World" of image ...