A two-qubit HQNN achieves 99.7% synthetic and 97% real accuracy on radar occupancy classification with up to 170x fewer parameters than CNNs, showing structural efficiency via ablation.
Dopplernet: a convolutional neural network for recognising targets in real scenarios using a persistent range–doppler radar,
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Indoor Occupancy Classification using a Compact Hybrid Quantum-Classical Model Enabled by a Physics-Informed Radar Digital Twin
A two-qubit HQNN achieves 99.7% synthetic and 97% real accuracy on radar occupancy classification with up to 170x fewer parameters than CNNs, showing structural efficiency via ablation.