Abstract Pattern Image Generation using Generative Adversarial Networks

التفاصيل البيبلوغرافية
العنوان: Abstract Pattern Image Generation using Generative Adversarial Networks
المؤلفون: Mahyoub, Mohamed, Abdulhussain, Sadiq H., Natalia, Friska, Sudirman, Sud, Mahmmod, Basheera M.
سنة النشر: 2023
مصطلحات موضوعية: 006.3 Artificial Intelligence, Machine Learning, Pattern Recognition, Data Mining
الوصف: pattern is very commonly used in the textile and fashion industry. Pattern design is an area where designers need to come up with new and attractive patterns every day. It is very difficult to find employees with a sufficient creative mindset and the necessary skills to come up with new unseen attractive designs. Therefore, it would be ideal to identify a process that would allow for these patterns to be generated on their own with little to no human interaction. This can be achieved using deep learning models and techniques. One of the most recent and promising tools to solve this type of problem is Generative Adversarial Networks (GANs). In this paper, we investigate the suitability of GAN in producing abstract patterns. We achieve this by generating abstract design patterns using the two most popular GANs, namely Deep Convolutional GAN and Wasserstein GAN. By identifying the best-performing model after training using hyperparameter optimization and generating some output patterns we show that Wasserstein GAN is superior to Deep Convolutional GAN.
نوع الوثيقة: conference object
وصف الملف: text
اللغة: English
Relation: https://kc.umn.ac.id/id/eprint/27048/1/Abstract%20Pattern%20Image%20Generation%20using%20Generative%20Adversarial%20Networks.pdf; Mahyoub, Mohamed and Abdulhussain, Sadiq H. and Natalia, Friska and Sudirman, Sud and Mahmmod, Basheera M. (2023) Abstract Pattern Image Generation using Generative Adversarial Networks. In: 2023 15th International Conference on Developments in eSystems Engineering (DeSE).
الاتاحة: https://kc.umn.ac.id/id/eprint/27048/
https://kc.umn.ac.id/id/eprint/27048/1/Abstract%20Pattern%20Image%20Generation%20using%20Generative%20Adversarial%20Networks.pdf
https://ieeexplore.ieee.org/document/10099871
رقم الانضمام: edsbas.940EF935
قاعدة البيانات: BASE