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Deep Learning Architecture Designer System Using Visual Blocks for User-Friendly Model Creation

Parole chiave ARTIFICIAL INTELLIGENCE, DEEP LEARNING, DEVELOPERS, HUMAN COMPUTER INTERACTION, MACHINE LEARNING, MODEL, USER INTERFACE, VISUAL PROGRAMMING

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 Deep learning has revolutionized numerous areas of research and application, with architectures of varying complexity being designed for different tasks. However, creating these architectures often requires expertise in specific libraries and a deep understanding of neural networks, making it inaccessible to many. The advent of visual programming and block-based interfaces provides an opportunity to bridge this gap.

This thesis aims to design and implement of a deep learning architecture designer system that uses visual blocks, making the process of building machine learning models more accessible and intuitive, especially for those without a deep technical background.
The main goals of this thesis are:
1. Review and understand the current state of the art in deep learning architectures and visual block-based design interfaces.
2. Design and implement a deep learning architecture designer system using visual blocks.
3. Conduct user testing with a small pool of users to evaluate the system's usability and efficiency.

If satisfactory, the result of the thesis will be released as an open-source project.

Conoscenze richieste Knowledge in deep learning frameworks (e.g., TensorFlow, PyTorch) is beneficial.
Experience with UI/UX design will be advantageous.


Scadenza validita proposta 11/03/2024      PROPONI LA TUA CANDIDATURA




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