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.
Hybrid dcnn–transfer learning model coupled with background clutter mitigation for fmcw radar-based people counting improvement,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
quant-ph 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
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.