GAN 2020: GAN (Generative Adversarial Networks) for Image-to-Image Translation |
Website | https://sites.google.com/view/gan2020/home |
Submission link | https://easychair.org/conferences/?conf=gan2020 |
Abstract registration deadline | May 15, 2020 |
Submission deadline | July 30, 2020 |
With recent breakthroughs in machine learning, we are witnessing many groundbreaking AI-based applications every day. Among all the new evolved concepts, GAN (Generative Adversarial Network) is the most exciting and futuristic approach. Facebook’s AI research director, YannLeCun, called GAN “the most interesting idea in the last ten years in ML.” GAN is helpful in generating output very close to the output generated by humans in a fraction of second, and it can efficiently produce high-quality music, speech, and images. In 2018, a GAN system generated a painting Edmond de Belamy which was later sold for US$432,500.
A typical GAN system consists of two neural networks, i.e., generator and discriminator, both of these network contests with each other, similar to game theory. The generator is responsible for generating quality images that should resemble ground truth, and the discriminator is accountable to identify if the generated image is a real image or fake image generated by the generator.
This book provides a comprehensive overview of the GAN (Generative Adversarial Network) concept starting from the original GAN network to various derived GAN based systems like Deep Convolutional GANs (DCGANs), Conditional GANs (cGANs), StackGAN, Wasserstein GANs(WGAN), cyclical GAN, etc. It also goes into detail of different real-life applications and common projects build around the GAN system with respective python codes.
Submission Guidelines
All the contributors are invited to submit their abstract of 700-100 words clearly explaining the abstract and table of contents on or before May 15, 2020 via Easy Chair Link: . All submitted chapters will be reviewed on a double-blind review basis. Contributors may also be requested to serve as reviewers for this book project. Authors will be notified by May 30, 2020 about the decision of their chapter.
The following paper categories are welcome:
- Full abstract defining the Proposal, Table of Contents, Author Names and Keywords
List of Topics
- Artificial Intelligence for GAN
- Machine Learning using GAN
- Deep Learning and GAN
- Image Generation using GAN
- Big Data and Data Analytics and GAN
- Cloud Computing and GAN
- Digital Transformation and GANE-Commerce and GAN
- Artistic Neural Networks and GAN
- Unsupervised Learning and GAN
- Natural Language Processing using GAN
- Pattern Recognition using GAN
- Image and Video Processing using GAN
- e-Learning/Ubiquitous Learning using GAN
- Business Intelligence and GAN
Editors
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Dr. Anand Nayyar, Duy Tan University, Da Nang, Viet Nam
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Dr. Arun Solanki, Gautam Buddha University, India
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Mohd Naved, Jagannath University, India
Publication
GAN 2020 proceedings will be published by Elsevier and the Chapters will be Indexed in SCOPUS, GOOGLE Scholar and other Major Indexing Services.
Contact
All questions about submissions should be emailed to ...
Dr. Anand Nayyar...Email: anandnayyar@duytan.edu.vn; Mobile (WhatsApp): +91-9878327635
Dr. Arun Solanki...Email: ymca.arun@gmail.com ; Mobile: +91-9650906633