Quantum Neural Network Classification Benchmark
Quantum Convolutional Neural Network (QCNN) · Machine-learning · 10 qubits · Qiskit Machine Learning, PennyLane, TensorFlow Quantum
Benchmark comparing quantum neural network architectures for image classification tasks on standard datasets including MNIST and Fashion-MNIST. Fully parameterized QCNNs achieve excellent classification accuracy despite a small number of free parameters. Comparative studies evaluate noise robustness across different QCNN model structures, data encoding methods, and optimizers under realistic quantum noise channels.
Benchmark comparing quantum neural network architectures for image classification tasks on standard datasets including MNIST and Fashion-MNIST. Fully parameterized QCNNs achieve excellent classification accuracy despite a small number of free parameters. Comparative studies evaluate noise robustness across different QCNN model structures, data encoding methods, and optimizers under realistic quantum noise channels.
Demonstrates that fully parameterized QCNNs achieve strong classification with far fewer parameters than classical counterparts, and evaluates noise robustness.
Simulator / hardware-agnostic
Qiskit Machine Learning, PennyLane, TensorFlow Quantum