Add to ORKGThis short paper presents what is currently the main challenge associated with using Generative Adversarial Networks (GANs) to generate visual media. That challenge is around automatically determining the authenticity of an image/video, which is of increasing importance as fake videos and images start to proliferate on social media, especially when associated with political campaigning. The paper introduces GANs, outlines how they are used to generate visual media and summarises this major challenge
Recently generative adversarial networks are becoming the main focus area of machine learning. It wa...
Applications of Generative Machine Learning techniques such as Generative Adversarial Networks (GANs...
Technologies for producing and modifying content for multimedia have reached to the point that they ...
This short paper presents what is currently the main challenge associated with using Generative Adve...
In recent years, there has been intense research on the generation of synthetic media, and a large n...
We live in a world made up of different objects, people, and environments interacting with each othe...
This electronic version was submitted by the student author. The certified thesis is available in th...
Image editing encompasses the process of altering images, and has been an active and interdisciplina...
In recent years, frameworks that employ Generative Adversarial Networks (GANs) have achieved immense...
Content creation aims to make the information (i.e., ideas, thoughts) accessible to the audience thr...
Since their introduction in 2014 Generative Adversarial Networks (GANs) have been employed successfu...
Generative Adversarial Networks, or GANs, build upon the foundation of machine learning by introduci...
EDITH is a project aiming to orchestrate an ecosystem of manipulation of reliable and safe data, app...
In Today’s date plagiarism is a very important aspect because content originality is the client's pr...
In recent years, frameworks that employ Generative Adversarial Networks (GANs) have achieved immense...
Recently generative adversarial networks are becoming the main focus area of machine learning. It wa...
Applications of Generative Machine Learning techniques such as Generative Adversarial Networks (GANs...
Technologies for producing and modifying content for multimedia have reached to the point that they ...
This short paper presents what is currently the main challenge associated with using Generative Adve...
In recent years, there has been intense research on the generation of synthetic media, and a large n...
We live in a world made up of different objects, people, and environments interacting with each othe...
This electronic version was submitted by the student author. The certified thesis is available in th...
Image editing encompasses the process of altering images, and has been an active and interdisciplina...
In recent years, frameworks that employ Generative Adversarial Networks (GANs) have achieved immense...
Content creation aims to make the information (i.e., ideas, thoughts) accessible to the audience thr...
Since their introduction in 2014 Generative Adversarial Networks (GANs) have been employed successfu...
Generative Adversarial Networks, or GANs, build upon the foundation of machine learning by introduci...
EDITH is a project aiming to orchestrate an ecosystem of manipulation of reliable and safe data, app...
In Today’s date plagiarism is a very important aspect because content originality is the client's pr...
In recent years, frameworks that employ Generative Adversarial Networks (GANs) have achieved immense...
Recently generative adversarial networks are becoming the main focus area of machine learning. It wa...
Applications of Generative Machine Learning techniques such as Generative Adversarial Networks (GANs...
Technologies for producing and modifying content for multimedia have reached to the point that they ...