A hybrid QCNN that reuses measurements from qubits discarded during pooling reports large accuracy gains on small image benchmarks, but the baseline is not matched in classical capacity.
The reduced register is processed by the next two convolutional layers, which integrate information across a larger effec- tive receptive field
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Hybrid Quantum-Classical Learning for Multiclass Image Classification
A hybrid QCNN that reuses measurements from qubits discarded during pooling reports large accuracy gains on small image benchmarks, but the baseline is not matched in classical capacity.