Quantum feature maps from trained VQCs boost land-cover classification performance when reused in classical kernel-based frameworks, though linear-readout VQCs fail to surpass RBF-SVM baselines on EuroSAT-MS.
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Parameterized Quantum Circuits as Feature Maps: Representation Quality and Readout Effects in Multispectral Land-Cover Classification
Quantum feature maps from trained VQCs boost land-cover classification performance when reused in classical kernel-based frameworks, though linear-readout VQCs fail to surpass RBF-SVM baselines on EuroSAT-MS.