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Circuits and graphs recognition using Artificial Intelligence and Machine Learning techniques.

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Circuits and graphs recognition using Artificial Intelligence and Machine Learning techniques.

Rel. Stefano Grivet Talocia. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2024

Abstract:

The rapid evolution of Artificial Intelligence (AI) and Machine Learning (ML) techniques has paved the way for innovative applications in various domains. This thesis explores the intersection of AI and ML in the realms of circuit and graph recognition. The objective is to develop intelligent systems capable of automatically identifying and understanding circuits and graphs, reducing human intervention in these complex tasks. The proposed approach leverages advanced deep learning models and neural networks to analyze and interpret visual representations of circuits and graphs. Image recognition algorithms are employed to identify components, connections, and patterns within the visual data, while graph-based models aid in understanding the underlying structures. The training of these models involves a diverse dataset, encompassing a wide range of circuit configurations and graph types.

Relators: Stefano Grivet Talocia
Academic year: 2023/24
Publication type: Electronic
Number of Pages: 103
Additional Information: Tesi secretata. Fulltext non presente
Subjects:
Corso di laurea: Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica)
Classe di laurea: New organization > Master science > LM-25 - AUTOMATION ENGINEERING
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/31028
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