WiMi Hologram Cloud, a leading global Hologram Augmented Reality Technology provider, announced that they are researching the utilization of quantum computing to perform synthetic image generation and recognition through generative adversarial networks and convolutional neural networks, and they proposed a quantum generative adversarial network model.
Compared to traditional generative adversarial network models, the quantum generative adversarial network model researched by WiMi has shorter simulation time. This benefits from the parallel processing capability of quantum computing, enabling the model to converge quickly during the training process and greatly shortening the training cycle. At the same time, this model also has lower generator and discriminator losses. Generator and discriminator losses are important indicators for measuring the performance of generative adversarial networks; the lower the loss, the closer the images generated by the generator are to real images, and the higher the accuracy of the discriminator’s judgments. The quantum generative adversarial network model effectively reduces the losses of the generator and discriminator through the optimization of quantum algorithms and model structures, making the generated images possess better quality and realism.
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Additionally, WiMi also proposed a hybrid quantum-classical convolutional neural network model for detecting synthetic images generated by the quantum generative adversarial network model. This model combines quantum computing with classical convolutional neural networks, fully leveraging the advantages of both. In synthetic image classification tasks, accuracy and computation time are two key indicators. By utilizing the precise computational capabilities of quantum computing, the model can extract image features more accurately, thereby performing more precise classification of real images and generated synthetic images.
Quantum computing has powerful potential in advancing the field of synthetic image generation and classification. With the continuous development and improvement of quantum computing technology, the quantum generative adversarial network model and hybrid quantum-classical convolutional neural network model researched by WiMi are expected to find wide applications in more fields, bringing us more exciting and efficient digital experiences.
Source: PRNewswire