WiMi Hologram Cloud Inc. (NASDAQ: WiMi) is a global Hologram Augmented Reality technology provider with a new deep convolutional neural network designed for image recognition. The company has developed a model utilizing quantum parameterized circuits as its core computing structure, a departure from traditional deep learning approaches and a step toward harnessing quantum computing’s parallel processing capabilities. This technology addresses limitations in computational complexity, memory consumption, and training efficiency by combining quantum circuits with a quantum-classical hybrid training mechanism. The model uses quantum parameterized circuits as its core computing structure, performs feature extraction on image data through quantum convolutional layers, and utilizes a quantum classification layer to complete the final recognition task. The quantum feature fusion module can reduce some computational overhead compared to traditional methods. Quantum Parameterized Circuits for Image Recognition WiMi Hologram Cloud Inc. has demonstrated a quantum deep convolutional neural network achieving progress, signaling a deepening of the application of quantum machine learning in artificial intelligence tasks such as image recognition, and also provides a new research direction for the realization of future large-scale quantum intelligent computing systems. WiMi’s approach centers on a fundamentally different computational structure, quantum parameterized circuits, as the core of its deep convolutional neural network. The new model utilizes these circuits to perform feature extraction on image data through quantum convolutional layers, culminating in a quantum classification layer for final recognition. This architecture mirrors the hierarchical structure of classical deep convolutional neural networks, but crucially, it leverages the parallel computing capability of quantum circuits to enhance processing speed when handling high-dimensional data. The system begins by mapping classical image data into the quantum state space via a data encoding module, a necessary step as quantum computers operate on quantum state information. This conversion of pixel information into qubit probability amplitudes is achieved through