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A GAN-Based Model of Deepfake Detection in Social Media by Preeti, Manoj Kumar et al

DeepFake uses Generative+Adversarial Network for successfully switching the identities of two people. Large public databases and deep learning methods are now rapidly available because of the proliferation of easily accessible tools online. It has resulted in the emergence of very real appealing fake content that produced a bad impact and challenges for society to deal. Pre-trained generative adversarial networks (GANs) that can flawlessly substitute one person's face in a video or image for that other are proving supportive for implementing deepfake. This paper primarily presented a study of methods used to implement deepfake. Also, discuss the main deepfake's manipulation and detection techniques, and the implementation and detection of deepfake using Deep Convolution-based GAN models. A study of Comparative analyses of proposed GAN with other exiting GAN models using parameters Inception Score "IS"and Fréchet Inception Distance "FID"is also embedded. A

Adversarial networkDeep convolution basedInception scoreInception distanceDeep fakesDeep learningDigital forensicsAce manipulationFace recognitionGenerative adversarial networkImage visionMedia forensics

The Complete Playbook for Generative AI in Fashion | Case Study

The Complete Playbook for Generative AI in Fashion | Case Study
businessoffashion.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from businessoffashion.com Daily Mail and Mail on Sunday newspapers.

France generalRobbie barratHarry potterGoldman sachsGenerative adversarial networkMckinsey companyStable diffusionCasablanca parisAdversarial network

Conditional Generative Adversarial Networks for Domain Transfer: A Sur by Guoqiang Zhou, Yi Fan et al

Generative Adversarial Network (GAN), deemed as a powerful deep-learning-based silver bullet for intelligent data generation, has been widely used in multi-disciplines. Furthermore, conditional GAN (CGAN) introduces artificial control information on the basis of GAN, which is more practical for many specific fields, though it is mostly used in domain transfer. Researchers have proposed numerous methods to tackle diverse tasks by employing CGAN. It is now a timely and also critical point to review these achievements. We first give a brief introduction to the principle of CGAN, then focus on how to improve it to achieve better performance and how to evaluate such performance across the variants. Afterward, the main applications of CGAN in domain transfer are presented. Finally, as another major contribution, we also list the current problems and challenges of CGAN.

Generative adversarial networkAdversarial networkConditional generative adversarial networkYcle consistencyDomain transferLoss functionRogressive enhancement mechanism

Fusion of Fashion & Technology Trends and Expectations

Read article about The use of AI-based software in designing clothes is being experimented with for the past five to six years as many professional fashion designers and computer scientists have taken up the task of bridging the human computer disconnects in conventional fashion designing. Generative Adversarial Network is the technology used today to make designing less subjective. and more articles about Textile industary at Fibre2Fashion

United statesAmber joe slootenLos angelesStella mccartneyHugo bossKarl lagerfeldRalph laurenLouis vuittonMaterial innovations initiativeApe yacht clubGenerative adversarial networkDolce gabbanaLululemon athleticaBored ape yacht clubAdversarial networkAmazon style

Fake faces created by AI look MORE trustworthy than real people, study reveals

Synthetically generated faces are not only highly photo realistic, but nearly indistinguishable from real faces and are even judged to be more trustworthy, researchers in Lancaster and California report.

United statesHany faridUniversity of californiaGenerative adversarial networkSophiej nightingale at lancaster universityProceedings of the national academy sciencesAdversarial networkLancaster universitySouth asianNational academy