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Parameter efficient hybrid spiking-quantum convolutional neural network with surrogate gradient and quantum data-reupload
This paper introduces the Spiking-Quantum Data Re-upload Convolutional Neural Network (SQDR-CNN), a novel architecture that enables joint training of spiking neural networks and quantum circuits. The model achieves competitive accuracy with significantly fewer parameters than state-of-the-art SNN baselines, showcasing the potential of hybrid neuromorphic and quantum systems for efficient machine learning.