Nasdaq

MicroAlgo Inc. Develops Quantum Convolutional Neural Network (QCNN) Architecture to Enhance the Performance of Traditional Computer Vision Tasks Using Quantum Mechanics Principles

SHENZHEN, China, May 12, 2025 /PRNewswire/ -- MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), they announced today their research on quantum visual computing, exploring the integration ...
Seeking Alpha

WiMi Studies Quantum Dilated Convolutional Neural Network Architecture

BEIJING, Oct. 13, 2025 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced that ...
Time

Convolutional Neural Networks (CNNs)

This article is published by AllBusiness.com, a partner of TIME. A Convolutional Neural Network (CNN) represents a sophisticated advancement in artificial intelligence technology, specifically ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
inc42

What Are Convolutional Neural Networks? Here’s All You Need to Know

What Is A Convolutional Neural Network? A Convolutional Neural Network (CNN), or CovNet, is a powerful deep learning algorithm designed to analyse visual data like images and videos. Inspired by the ...
ascopubs.org

Performance analysis of artificial intelligence–driven convolutional neural network architectures for liver tumor segmentation.

Comparative efficacy and safety of donafenib versus bevacizumab in combination with immune checkpoint inhibitors and interventional therapy for advanced hepatocellular carcinoma: A retrospective ...
EurekAlert!

A novel deep learning model for medical image segmentation with convolutional neural network and transformer

Accurate segmentation of medical images is essential for clinical decision-making, and deep learning techniques have shown remarkable results in this area. However, existing segmentation models that ...