Image change detection device utilizing quantum machine learning and related methods

A change detection method comprising:

• encoding image data to generate a latent vector, and decode the latent vector to generate new image data, using a variational autoencoder (VAE);
• and
• using a controller in cooperation with at least one quantum computing circuit configured to perform quantum subset summing to
• generate a quantum reward matrix for a plurality of quantum neural network models using the at least one quantum computing circuit,
• select a quantum neural network model from the plurality of quantum neural network models based upon the new image data and the quantum reward matrix, and
• process the new image data using the selected quantum neural network model to detect changes therein.

A non-transitory computer-readable medium having computer-executable instructions for causing a controller to cooperate with and at least one quantum computing circuit configured to perform quantum subset summing to perform performs steps comprising:

• receiving from a variational autoencoder (VAE) new image data generated based upon encoding image data to generate a latent vector, and decoding the latent vector to generate the new image data;
• generating a quantum reward matrix for a plurality of quantum neural network models using the at least one quantum computing circuit;
• selecting a quantum neural network model from the plurality of quantum neural network models based upon the new image data and the quantum reward matrix;
• and
• processing the new image data using the selected quantum neural network model to detect changes therein.