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Generative Models in Artificial Intelligence and Their Applications II

This special issue belongs to the section “Computing and Artificial Intelligence“.

Special Issue Information

Dear Colleagues,

In recent years, artificial intelligence has been used to generate a significant amount of high-quality data, like images, music, and videos. The creation of such a vast amount of synthetic data was made possible due to the improved performance of different machine learning techniques, like artificial neural networks. Considering the increased interest in this area, new techniques for automatic data generation and augmentation were recently proposed. For instance, generative adversarial networks (GANs) and their variants are nowadays popular techniques in this research field. The creation of synthetic data was also achieved with evolutionary-based techniques, for instance in the context of multimedia artifacts creation. This Special Issue aims to collect new contributions in the area of generative models in artificial intelligence, focusing on their applications for addressing complex real-world problems in engineering, medicine, entertainment, manufacturing, optimization, business, and related fields. We kindly invite researchers and practitioners to contribute their high-quality original research or review articles on these topics to this Special Issue.

Dr. Mauro Castelli
Dr. Luca Manzoni
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • evolutionary computation
  • neuroevolution
  • generative models
  • data generation
  • data augmentation
  • images generation
  • algorithmic music
  • real-world applications

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Appl. Sci. - ISSN 2076-3417