Add to ORKGRecently generative adversarial networks are becoming the main focus area of machine learning. It was first introduced by Ian Goodfellow in 2014. The structure of GAN consists of two neural networks, which are constantly competing with each other: generator and discriminator. One learns to produce fake samples similar to the training data and the other tries to differentiate between fake and real data samples. The goal is to train the discriminator using samples from a known dataset until it reaches a good level of accuracy. Training GANs are challenging and can be time taking, but the result is quite impressive. GANs are being used in many industries, for instance, games, films, and medicine and for any distribution of data such as images,...
University of Technology Sydney. Faculty of Engineering and Information Technology.A main goal of st...
In recent years, Generative Adversarial Networks (GANs) have become a hot topic among researchers an...
Applications of Generative Machine Learning techniques such as Generative Adversarial Networks (GANs...
As a new unsupervised learning algorithm framework, generative adversarial networks (GAN) has been f...
Since their introduction in 2014, Generative Adversarial Networks (GAN), have been a hot topic in th...
Since the birth of generative adversarial networks (GANs), the research on it has become a hot spot ...
Generative Adversarial Networks (GANs) continue to be one of the most popular deep learning approach...
GANs (generative opposing networks) are a technique for learning deep representations in the absence...
Generating synthetic data is a relevant point in the machine learning community. As accessible data ...
Generating synthetic data is a relevant point in the machine learning community. As accessible data ...
Generative Adversarial Networks (GANs) have proven to be efficient systems for data generation and o...
Since their introduction in 2014 Generative Adversarial Networks (GANs) have been employed successfu...
Computer vision is one of the hottest research fields in deep learning. The emergence of generative ...
In recent years, Generative Adversarial Network (GAN) and its variants have gained great popularity ...
Deep learning artificial neural networks are implemented in machines at an increasing rate in order ...
University of Technology Sydney. Faculty of Engineering and Information Technology.A main goal of st...
In recent years, Generative Adversarial Networks (GANs) have become a hot topic among researchers an...
Applications of Generative Machine Learning techniques such as Generative Adversarial Networks (GANs...
As a new unsupervised learning algorithm framework, generative adversarial networks (GAN) has been f...
Since their introduction in 2014, Generative Adversarial Networks (GAN), have been a hot topic in th...
Since the birth of generative adversarial networks (GANs), the research on it has become a hot spot ...
Generative Adversarial Networks (GANs) continue to be one of the most popular deep learning approach...
GANs (generative opposing networks) are a technique for learning deep representations in the absence...
Generating synthetic data is a relevant point in the machine learning community. As accessible data ...
Generating synthetic data is a relevant point in the machine learning community. As accessible data ...
Generative Adversarial Networks (GANs) have proven to be efficient systems for data generation and o...
Since their introduction in 2014 Generative Adversarial Networks (GANs) have been employed successfu...
Computer vision is one of the hottest research fields in deep learning. The emergence of generative ...
In recent years, Generative Adversarial Network (GAN) and its variants have gained great popularity ...
Deep learning artificial neural networks are implemented in machines at an increasing rate in order ...
University of Technology Sydney. Faculty of Engineering and Information Technology.A main goal of st...
In recent years, Generative Adversarial Networks (GANs) have become a hot topic among researchers an...
Applications of Generative Machine Learning techniques such as Generative Adversarial Networks (GANs...