The Improved DCGAN framework - Enhancing the quality of generated images and stabilizing the training of Deep Convolutional Generative Adversarial Networks

dc.contributor.advisor	Hetland, Magnus Lie
dc.contributor.author	Sjøberg, Claudia Laila
dc.date.accessioned	2019-09-11T10:55:41Z
dc.date.created	2018-08-17
dc.date.issued	2018
dc.identifier	ntnudaim:18171
dc.identifier.uri	http://hdl.handle.net/11250/2615795
dc.description.abstract	Using current state-of-the-art algorithms to improve the DCGAN model with regard to image quality and training stability.	en
dc.language	eng
dc.publisher	NTNU
dc.subject	Datateknologi, Algoritmer og HPC	en
dc.title	The Improved DCGAN framework - Enhancing the quality of generated images and stabilizing the training of Deep Convolutional Generative Adversarial Networks	en
dc.type	Master thesis	en
dc.source.pagenumber	125
dc.contributor.department	Norges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi og elektroteknikk,Institutt for datateknologi og informatikk	nb_NO
dc.date.embargoenddate	10000-01-01