StreetInsider.com News Articles

WiMi develops quantum-classical neural network for image classification

Wed, 18 Feb 2026 08:00:36 -0500

WiMi Hologram Cloud Inc. (NASDAQ: WIMI) announced the development of a hybrid quantum-classical Inception neural network model for image classification, according to a company press release.

The Beijing-based hologram technology provider said the model integrates quantum computing with classical deep learning through three parallel feature extraction paths. The quantum path uses multi-dimensional quantum circuits to process local image regions, while the classical path employs conventional convolution networks for stability. A hybrid path combines classical features with quantum processing.

The company stated that quantum features are encoded using parameterized rotation gates that map image blocks to multi-qubit rotation angles. The quantum circuits incorporate

WiMi Studies Hybrid Quantum-Classical Inception Neural Network Model for Image Classification

Wed, 18 Feb 2026 08:00:00 -0500

BEIJING, Feb. 18, 2026 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, proposed a brand-new technological innovation—a hybrid quantum-classical Inception neural network model for image classification. This is a brand-new hybrid architecture that naturally integrates quantum computing with classical deep learning through Inception-style parallel feature channels, achieving triple improvements in performance, efficiency, and robustness. The core goal of this technology is to utilize the high-dimensional feature expression capability of quantum computing to solve the expressiveness bottleneck of image

WiMi Studies Hybrid Quantum-Classical Inception Neural Network Model for Image Classification

Wed, 18 Feb 2026 08:00:00 -0500

WiMi Studies Hybrid Quantum-Classical Inception Neural Network Model for Image Classification

Wed, 18 Feb 2026 08:00:00 -0500

WiMi Studies Hybrid Quantum-Classical Inception Neural Network Model for Image Classification

Wed, 18 Feb 2026 08:00:00 -0500

WiMi releases hybrid quantum-classical neural network for image classification

Fri, 06 Feb 2026 08:31:00 -0500

WiMi Hologram Cloud Inc. (NASDAQ: WIMI) announced the release of a Hybrid Quantum-Classical Neural Network (H-QNN) technology for MNIST binary image classification. The technology combines quantum computing elements with traditional neural networks to process handwritten digit recognition tasks.

The H-QNN system consists of three components: a data preprocessing module, a quantum encoding and feature extraction module, and a classical neural classifier. The preprocessing module converts 28×28 pixel MNIST images into a format suitable for quantum processing through binarization and normalization operations.

The quantum component uses Parameterized Quantum Circuits (PQC) containing rotation gates and entanglement gates to map image data into quantum states.

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

Fri, 06 Feb 2026 08:30:00 -0500

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

BEIJING, Feb.06, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced the release of a Hybrid Quantum-Classical Neural Network (Hybrid Quantum-Classical Neural Network, H-QNN) technology for efficient MNIST binary image classification. This breakthrough achievement marks a new progress in quantum machine learning moving from theoretical exploration toward practicalization, and also embodies the enterprise's core competitiveness in the field of quantum intelligent algorithm research.

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

Fri, 06 Feb 2026 08:30:00 -0500

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

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

Fri, 06 Feb 2026 08:30:00 -0500

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

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

Fri, 06 Feb 2026 08:30:00 -0500

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

WiMi develops quantum-classical hybrid neural network for image tasks

Thu, 15 Jan 2026 09:51:09 -0500

WiMi Hologram Cloud Inc. (NASDAQ: WIMI) announced the development of a Lean Classical-Quantum Hybrid Neural Network framework designed for image classification applications. The Beijing-based augmented reality technology company said the system combines classical computing with quantum circuits to process visual data.

The LCQHNN framework divides processing between classical front-end components for initial feature extraction and quantum back-end systems using variational quantum circuits for classification decisions. The quantum portion employs a four-layer variational quantum circuit structure containing parameterized rotation gates, controlled gates, and entanglement operations.

According to the company, the system processes images through several stages. Classical convolutional layers first extract local features

WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification

Thu, 15 Jan 2026 09:50:00 -0500

Beijing, Jan. 15, 2026 (GLOBE NEWSWIRE) -- WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification

BEIJING, Jan. 15, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, proposed a brand-new Lean Classical-Quantum Hybrid Neural Network (LCQHNN) framework, aimed at achieving maximized learning efficiency with the smallest possible quantum circuit structure. This technology balances implementability and performance superiority in its design, marking a key step for quantum neural networks from theoretical feasibility toward practical deployment.
The core idea of LCQHNN is to center on

WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification

Thu, 15 Jan 2026 09:50:00 -0500

Beijing, Jan. 15, 2026 (GLOBE NEWSWIRE) -- WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification

WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification

Thu, 15 Jan 2026 09:50:00 -0500

Beijing, Jan. 15, 2026 (GLOBE NEWSWIRE) -- WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification

WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification

Thu, 15 Jan 2026 09:50:00 -0500

Beijing, Jan. 15, 2026 (GLOBE NEWSWIRE) -- WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification

WiMi introduces quantum neural network for multi-channel data processing

Mon, 05 Jan 2026 10:51:56 -0500

WiMi Hologram Cloud Inc. (NASDAQ: WIMI) announced the launch of its Quantum Convolutional Neural Network for Multi-Channel Supervised Learning (MC-QCNN) technology. The company said the technology enables quantum models to process multi-channel data for applications in image classification, medical imaging, video analysis, and multimodal monitoring.

The technology uses parameterized quantum gates to create convolution operators that can handle complex functions while maintaining resistance to quantum decoherence. Unlike traditional convolution methods that slide within pixel neighborhoods, WiMi's approach compresses and encodes data from multiple channels into quantum state amplitudes, phases, or entanglement structures.

The quantum multi-channel convolution operator uses parameterized rotation gates and

WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning

Mon, 05 Jan 2026 10:50:00 -0500