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Generative Methods to Enhance Creativity in User Interface Design

Parole chiave GENERATIVE ADVERSARIAL NETWORKS, HUMAN-COMPUTER INTERACTION, MACHINE LEARNING, USER EXPERIENCE, USER INTERFACE

Riferimenti LUIGI DE RUSSIS

Riferimenti esterni Tommaso CalÚ

Gruppi di ricerca DAUIN - GR-10 - Intelligent and Interactive Systems - e-LITE

Tipo tesi EXPERIMENTAL, RESEARCH

Descrizione This thesis focuses on the use of generative methods to enhance creativity in User Interface (UI) design. The emergence of generative methods, particularly deep learning techniques, has provided new opportunities for computer-aided design. Recent developments in generative adversarial networks (GANs) and autoencoders have shown promising results in generating creative content in various domains such as graphics, music, and text. However, the application of these methods in the field of UI design remains largely unexplored.

UI design is a critical aspect of software development that greatly impacts user experience. However, the design process can be challenging due to the necessity of considering multiple factors, such as aesthetic appeal, usability, and accessibility. Generative methods have the potential to provide designers with novel and innovative design options, enhancing their creativity and supporting them in overcoming design challenges.

The main goals of this thesis are:
* Review the current state of the art in generative methods and their applications in creative design.
* Develop a generative model for UI design that can provide creative and usable design options.
* Evaluate the effectiveness and usability of the generated designs through user studies.

Vedi anche  generative methods to enhance creativity in user interface design.pdf 

Conoscenze richieste Good programming skills and Python knowledge are required.


Scadenza validita proposta 17/05/2024      PROPONI LA TUA CANDIDATURA




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