The week's pick
Random Articles
Reseach Article
Survey Paper on Applications of Generative Adversarial Networks in the Field of Social Media
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 175 - Number 20 |
| Year of Publication: 2020 |
| Authors: Ananya Malik |
10.5120/ijca2020920728
|
Ananya Malik . Survey Paper on Applications of Generative Adversarial Networks in the Field of Social Media. International Journal of Computer Applications. 175, 20 ( Sep 2020), 13-18. DOI=10.5120/ijca2020920728
Abstract
Social Media today is one of the most widely known terms. If the internet is the window to the world, social media is what actually has brought people from all over the world together. Today one can easily sit in the comfort of their homes and actively engage in an impactful political movement, taking place on the other end of the world. Social Media has enabled and impacted a myriad of fields. It has been a big aggressor in political movements, where candidates direct a major investment both in terms of time and money towards spreading the popularity of their campaign on social media websites. It has impacted major movements in recent times and brought out path-breaking societal changes. Social Media has provided companies with a new route of targeting their advertisements and has brought them closer to their customers and shareholders. Social Media has also opened up a new path of careers for many. Amongst all these positives, social media possess multiple challenges as well which include but are not limited to cyberbullying, privacy attacks and peer pressure which results in alarming rates of mental health detrition. The Generative Adversarial Nets is an extremely nascent but fast-growing network architecture in Deep Learning. This paper explores different forms of GANs and their applications in Social Media.
References
- Generative Adversarial Nets, Ian J. Goodfellow, Jean Pouget-Abadie∗ , Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair† , Aaron Courville, Yoshua Bengio‡ Departement d’informatique et de recherche op ´ erationnelle ´ Universite de Montr ´ eal ´ Montreal, QC H3C 3J7
- Abdullah-All-Tanvir, E. M. Mahir, S. Akhter and M. R. Huq, "Detecting Fake News using Machine Learning and Deep Learning Algorithms," 2019 7th International Conference on Smart Computing & Communications (ICSCC), Sarawak, Malaysia, Malaysia, 2019, pp. 1-5, doi: 10.1109/ICSCC.2019.8843612.
- A computationally intelligent agent for detecting fake news using generative adversarial networks Srinidhi Hiriyannaiah1 , A.M.D. Srinivas1 , Gagan K. Shetty1 , Siddesh G.M.2 and K.G. Srinivasa3 1 Department of CSE, Ramaiah Institute of Technology, Bangalore, India 2 Department of ISE, Ramaiah Institute of Technology, Bangalore, India 3 Department of Information Management & Coordination, NITTTR, Chandigarh, India
- Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks Emily Denton∗ Dept. of Computer Science Courant Institute New York University Soumith Chintala∗ Arthur Szlam Rob Fergus Facebook AI Research New York
- Yu, Shiqi & Chen, Haifeng & Garcia, Edel & Poh, Norman. (2017). GaitGAN: Invariant Gait Feature Extraction Using Generative Adversarial Networks. 532-539. 10.1109/CVPRW.2017.80.
- Y. Choi, M. Choi, M. Kim, J. Ha, S. Kim and J. Choo, "StarGAN: Unified Generative Adversarial Networks for Multi-domain Image-to-Image Translation," 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, 2018, pp. 8789-8797, doi: 10.1109/CVPR.2018.00916.
- Wasserstein GAN Martin Arjovsky1 , Soumith Chintala2, and L´eon Bottou1,2 1Courant Institute of Mathematical Sciences 2Facebook AI Research
- AttGAN: Facial Attribute Editing by Only Changing What You Want Zhenliang He, Wangmeng Zuo, Senior Member, IEEE, Meina Kan, Member, IEEE, Shiguang Shan, Senior Member, IEEE, and Xilin Chen, Fellow, IEEE
- PCGAN: Partition-Controlled Human Image Generation Dong Liang∗ , Rui Wang∗†, Xiaowei Tian, Cong Zou SKLOIS, Institute of Information Engineering, Chinese Academy of Sciences School of Cyber Security, University of Chinese Academy of Sciences {liangdong, wangrui, tianxiaowei, zoucong}@iie.ac.cn
- Semantic Photo Manipulation with a Generative Image Prior (to appear at SIGGRAPH 2019) David Bau, Hendrik Strobelt, William Peebles, Jonas Wulff, Bolei Zhou, Jun-Yan Zhu, Antonio Torralba.
- PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION Tero Karras NVIDIA {tkarras,taila,slaine,jlehtinen}@nvidia.com Timo Aila NVIDIA Samuli Laine NVIDIA Jaakko Lehtinen NVIDIA and Aalto University
Index Terms
Keywords