WiMi Develops Quantum Hybrid Neural Network Model for Intelligent Image Classification

WiMi Hologram Cloud proposed a Lean Classical-Quantum Hybrid Neural Network (LCQHNN) framework, combining classical stability optimization with quantum feature amplification to improve learning efficiency and minimize quantum circuit structure. The network consists of a classical front-end for feature extraction and a quantum back-end for nonlinear mapping and classification. Experiments show that a four-layer variational quantum circuit can achieve comparable or better performance than deep VQCs, significantly reducing resource consumption and error accumulation risk.