Through this article, we have seen how QCNN uses a CNN model and a quantum computing environment to enable a variety of approaches in the field. Fully parameterized quantum convolutional neural networks open up promising results for quantum machine learning and data science applications. Apart from this discussion, if you want to look at a practical implementation of the QCNN, I recommend that you look at the TensorFlow implementation and the researcher’s team as mentioned in the introduction.
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