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WiMi unveils quantum neural network for image classification

Mon, 20 Jul 2026 09:02:05 -0400

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) announced the release of a quantum convolutional neural network (QCNN) for image classification, built on quantum random access memory (QRAM) architecture, according to a company statement dated July 20, 2026.

The technology targets large-scale image classification tasks and is designed to address limitations in existing QCNN models, specifically qubit count, circuit depth, and data loading efficiency. Current quantum computing devices face constraints including limited qubit availability and high noise levels, which hinder the processing of large-scale input data.

In WiMi's approach, QRAM is integrated into the feature extraction and channel mapping process of the QCNN rather

WiMi unveils quantum neural network for image classification

Mon, 20 Jul 2026 09:02:05 -0400

In WiMi's approach, QRAM is integrated into the feature extraction and channel mapping process of the QCNN rather

WiMi Releases Resource-Efficient Quantum Convolutional Neural Network Based on QRAM, Accelerating the Practical Implementation of Large-Scale Image Classification Applications

Mon, 20 Jul 2026 09:00:00 -0400

BEIJING, July 20, 2026 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, announced the release of its latest independently developed achievement—a quantum convolutional neural network for efficient image classification based on quantum random access memory (QRAM). This technology is oriented toward typical image classification tasks with large-scale input data and multiple output channels. It systematically addresses the key bottlenecks of existing quantum convolutional neural networks in terms of the number of qubits, circuit depth, and data loading efficiency,

WiMi Releases Resource-Efficient Quantum Convolutional Neural Network Based on QRAM, Accelerating the Practical Implementation of Large-Scale Image Classification Applications

Mon, 20 Jul 2026 09:00:00 -0400

WiMi Releases Resource-Efficient Quantum Convolutional Neural Network Based on QRAM, Accelerating the Practical Implementation of Large-Scale Image Classification Applications

Mon, 20 Jul 2026 09:00:00 -0400

WiMi Releases Resource-Efficient Quantum Convolutional Neural Network Based on QRAM, Accelerating the Practical Implementation of Large-Scale Image Classification Applications

Mon, 20 Jul 2026 09:00:00 -0400

WiMi researches neural networks for quantum key distribution optimization

Mon, 29 Jun 2026 10:50:36 -0400

WiMi Hologram Cloud Inc. (NASDAQ: WIMI) announced it is researching the use of neural networks to optimize parameters in dual-field quantum key distribution (TF-QKD) systems, according to a press release from the Beijing-based company.

The research involves training and evaluating three neural network models: a Backpropagation Neural Network (BPNN), a Radial Basis Function Neural Network (RBFNN), and a Generalized Regression Neural Network (GRNN). Each model was tested for its ability to predict optimal parameter configurations for TF-QKD systems.

WiMi said all three models demonstrated the ability to predict optimal TF-QKD parameters, with RBFNN and GRNN showing higher prediction accuracy in high-dimensional parameter

WiMi Explores the Application of Neural Networks in Parameter Optimization for Dual-Field Quantum Key Distribution