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WiMi's Next-Generation Quantum Convolutional Neural Network Reshapes Classical Data Classification Methods

BEIJING, Aug. 21, 2026 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, proposes a cutting-edge quantum machine learning technology oriented toward classical data classification tasks—a quantum convolutional neural network with interaction layers for classical data classification. This technology systematically enhances the overall performance of quantum convolutional neural networks in terms of expressive power, entanglement generation capability, and actual classification performance by introducing a novel interaction layer structure based on three-qubit interactions, marking an important step forward in the structural design of quantum deep learning models toward a new phase driven by multi-body interactions.

WiMi Hologram Cloud Inc. Unveils H-QNN Technology for Efficient Binary MNIST Image Classification

BEIJING, Aug. 13, 2026 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WIMI" or the "Company"), a globally leading technology provider, announces a major breakthrough in releasing Hybrid Quantum Neural Network (H-QNN), an innovative hybrid quantum-classical neural network technology tailored for the image recognition sector. The technology creatively integrates parameterised quantum circuits with classical neural network architectures and has been successfully deployed for binary image classification tasks on the MNIST dataset, delivering outstanding performance in classification accuracy, feature representation capability, and model training efficiency.

WiMi Explores Federated Training Framework for Hybrid Quantum-Classical Machine Learning Models

BEIJING, Aug. 4, 2026 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, is exploring a federated training framework for hybrid quantum-classical machine learning models, deeply integrating quantum neural networks (QNN) with classical pre-trained convolutional models, achieving dual breakthroughs in model accuracy and training efficiency through a distributed quantum computing architecture, and opening up innovative technical paths for data privacy protection and large-scale model training. Quantum computers, through the superposition and entanglement states of qubits, can process an exponential number of computational tasks in parallel.