Autoencoder-generated MRI images of ASD and non-ASD patients: By designing and training the autoencoder model, this paper successfully generates MRI images for ASD and non-ASD patients. This method ...

(The first line shows the input images, and the second presents the ones generated by the autoencoder.) This project introduces an example of a convolutional (variational) autoencoder that reads an ...

Swapping Autoencoder consists of autoencoding (top) and swapping (bottom) operation.Top: An encoder E embeds an input (Notre-Dame) into two codes.The structure code is a tensor with spatial dimensions ...

At 1 sample per pixel (spp), the Monte Carlo integration of indirect illumination results in very noisy images, and the problem can therefore be framed as reconstruction instead of denoising. Previous ...

Similar to convolution neural networks, a convolutional autoencoder specializes in the learning of image data, and it uses a filter that is moved across the entire image section by section. The ...

A novel adversarial autoencoder (AAE) is then proposed as an SAR representation and generation network. It consists of a generator network that decodes target knowledge to SAR images and an ...

Google Photos could soon display IPTC credit metadata on images, which will be helpful in figuring out if an image is AI-generated or not. The changes are not currently live within Google Photos ...

To generate images on iPhone using Image Playground, ensure you have iOS 18.2 on a compatible device (iPhone 15 Pro or newer). Open the Playground app, enter a description for your image, ...