Exploring Bioimage Synthesis and Detection via Generative Adversarial Networks: A Multi-Faceted Case Study

Background:Generative Adversarial Networks (GANs), thanks to their great versatility, have a plethora of applications in biomedical imaging with the goal of simulating complex pathological conditions and creating clinical data used for training advanced machine learning models. The ability to genera...

Popoln opis

Bibliografske podrobnosti

Principais autores:	Valeria Sorgente, Dante Biagiucci, Mario Cesarelli, Luca Brunese, Antonella Santone, Fabio Martinelli, Francesco Mercaldo
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2025-06-01
Serija:	Journal of Imaging
Teme:	GAN convolutional generative adversarial network DCGAN deep convolutional generative adversarial network deep learning bioimages
Online dostop:	https://www.mdpi.com/2313-433X/11/7/214
Oznake:	Označite Brez oznak, prvi označite!