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Generative adversarial network
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Deep learning method
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11
Intraoperative Organ Motion Models with an Ensemble of Conditional Generative Adversarial Networks
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling
scientific article published in January 2016
Freehand Ultrasound Image Simulation with Spatially-Conditioned Generative Adversarial Networks
Spatial Orthogonal Attention Generative Adversarial Network for MRI Reconstruction
scientific article published on 27 October 2020
High quality and fast compressed sensing MRI reconstruction via edge-enhanced dual discriminator generative adversarial network
scientific article published on 21 December 2020
Predicting CO2 Plume Migration in Heterogeneous Formations Using Conditional Deep Convolutional Generative Adversarial Network
scientific article published in July 2019
LGAN: Lung segmentation in CT scans using generative adversarial network
scientific article published on 16 November 2020
A novel deep learning conditional generative adversarial network for producing angiography images from retinal fundus photographs
scientific article published on 09 December 2020
COVID-19 CT Image Synthesis with a Conditional Generative Adversarial Network
scientific article published on 04 December 2020
KT-GAN: Knowledge-Transfer Generative Adversarial Network for Text-to-Image Synthesis
scientific article published on 01 October 2020
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A generative adversarial network (GAN) is a class of machine learning frameworks and a prominent framework for approaching generative artificial intelligence. The concept was initially developed by Ian Goodfellow and his colleagues in June 2014. In a GAN, two neural networks compete with each other in the form of a zero-sum game, where one...

Subclass of
Neural network (machine learning)
Generative model
Generative artificial intelligence
Algorithm
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