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Requires implementation of the Quanvolutional Neural Network Layer structure.
Reference:
M. Henderson, S. Shakya, S. Pradhan, and T. Cook, “Quanvolutional Neural Networks: Powering Image Recognition with Quantum Circuits,” arXiv:1904.04767 [quant-ph], Apr. 2019, Available: https://arxiv.org/abs/1904.04767
The text was updated successfully, but these errors were encountered:
There also might be a need to build a QuanvolutionalNeuralNetwork class that implements the sequence abstract method and deals with measurement and results at the end of a QuanvolutionalLayer. The results received after the implementation of this layer are either processed classically (via some CNN) or need to be embedded again into a quantum circuit and processed with some QCNN structure.
Is the quanvolutional layer always applied as the first layer in the neural network structure? Why cannot it be applied in between, lets say, convolutional and pooling layer?
Requires implementation of the Quanvolutional
Neural NetworkLayer structure.Reference:
The text was updated successfully, but these errors were encountered: