New LaunchJul 30, 2026, 11:22 AM
MicroCloud Hologram Launches DSQ-Net for Noisy Image Classification
AI Summary
MicroCloud Hologram Inc. launched its Deep Spiking Quantum Neural Network (DSQ-Net), a hybrid quantum-classical deep learning system designed for noisy image classification. This technology integrates Variational Quantum Circuits directly into the training process of Deep Spiking Neural Networks, addressing challenges like non-differentiable spiking events. DSQ-Net demonstrated over 90% classification accuracy on noisy test images, with significantly slower performance degradation compared to classical models. The company, which has over 3 billion RMB in cash reserves, plans to invest more than $400 million USD in frontier technologies including quantum computing and AI AR.
Key Highlights
- Launched Deep Spiking Quantum Neural Network (DSQ-Net) for noisy image classification.
- DSQ-Net systematically introduces a Variational Quantum Circuit (VQC) auxiliary training mechanism.
- Directly embeds quantum circuits into Deep Spiking Neural Networks (SNN) training process.
- Achieves classification accuracy stably above 90% on unseen noisy test images.
- Performance degradation is noticeably slower as noise levels increase compared to classical SNN models.
- Company has cash reserves exceeding 3 billion RMB.
- Plans to invest over $400 million USD in blockchain, quantum computing, quantum holography, and AI AR.
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