In a study published in the journal Information Systems Research, Texas Tech University's Shuo Yu and his collaborators ...

Generative AI brings opportunities, but protecting your sensitive information must remain a top priority, so choosing the ...

Generative adversarial networks (GANs) are used for image enhancement such as single image super-resolution (SISR) and deblurring. The conventional GANs-based image enhancement suffers from two ...

Generative Adversarial Networks (GANs) have emerged as a powerful tool in artificial intelligence, particularly for unsupervised learning. This systematic review analyzes GAN applications in ...

Amazon's AWS recently lost a key vice president helping oversee generative artificial intelligence development as well as the company's Bedrock service, as the competition for talent heats up.

Solving life's great mysteries often requires detective work, using observed outcomes to determine their cause. For instance, nuclear physicists at the U.S. Department of Energy's Thomas Jefferson ...

Code release for the paper "GSGAN: Adversarial Learning for Hierarchical Generation of 3D Gaussian Splats" - hse1032/GSGAN ...

Specifically, a generative adversarial network with an improved loss function was employed to recover both the structural and color information of out-of-focus low-quality images. 2D MoS 2 grown by ...