UML Class Model Generation of Images Using Neural Networks
Irina-Gabriela Nedelcu, Anca Daniela Ioniţă, Stefan Alexandru Mocanu, Daniela Saru · 2022
This paper presents the way machine learning and deep learning techniques are used to classify boats and extract their attributes in a UML model. This is based on the development and the implementation of a classification and feature extraction application for boat types. The case study aims to explore the bridge between artificial intelligence algorithms for computer vision and the domain of object-oriented modeling. The paper describes methods applied to process the dataset and their labels to train a neural network model. The resulting model can classify boat types and provide their attributes, based on what can be identified in the image and output the textual result in a UML class diagram format.