Applied Artificial Intelligence Laboratory

Publicações

Natural Stone Image Classification Using Online Databases and Convolutional Neural Networks

Publication . Brito, J. H.; Morim, D. M.; Carvalho, Cristina Isabel Paulo; Alves, Raquel

ABSTRACT: In this paper, we discuss the relevance of two distinct types of online natural stone databases (technical-institutional repositories and logistics-commercial e-platforms) for extracting (training and testing) input images and creating an automatic visual inspection system for natural stone classification. Using convolutional neural networks (CNNs) and images from a selected online data repository, a Deep Learning (DL) system was developed to estimate the class of the natural stone in a given image. The DL models were developed through transfer learning from existing image classifiers, as pre-trained classifiers were retrained on our dataset. Our best model achieved an Accuracy of 70.3% and an F-score of 0.67 for 70 classes.

2025-06Comunicação em conferência

Acesso aberto

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Palavras-chave

Artificial Intelligence,Computer Vision,Machine Learning,Robotics, Engineering and technology

Entidade financiadora

Fundação para a Ciência e a Tecnologia, I.P.

Programa de financiamento

Concurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017/2018) - Financiamento Base

Número da atribuição

UIDB/05549/2020