Colors characterize each object around us. For this reason, the study of colors has played a key role in Artificial Intelligence (think, for instance, of image classification, object recognition and segmentation). However, there are some topics about colors still little explored. One of them concerns fabric colors. This is a particular topic since fabrics have some characteristics, such as specific textures, that are not found in other contexts. In this paper, we want to propose a new Convolutional Neural Network (CNN) based model for identifying fabric colors. After introducing this model, we consider three different versions of it and create an ensemble of the corresponding CNNs to get better results. Finally, through a series of experiments, we show that our ensemble is able to improve the state-of-the-art on the identification of fabric colors.

Defining a deep neural network ensemble for identifying fabric colors

Amelio A.
Primo
;
2022-01-01

Abstract

Colors characterize each object around us. For this reason, the study of colors has played a key role in Artificial Intelligence (think, for instance, of image classification, object recognition and segmentation). However, there are some topics about colors still little explored. One of them concerns fabric colors. This is a particular topic since fabrics have some characteristics, such as specific textures, that are not found in other contexts. In this paper, we want to propose a new Convolutional Neural Network (CNN) based model for identifying fabric colors. After introducing this model, we consider three different versions of it and create an ensemble of the corresponding CNNs to get better results. Finally, through a series of experiments, we show that our ensemble is able to improve the state-of-the-art on the identification of fabric colors.
2022
Inglese
130
109687
Classification of fabric colors; Color classification; Convolutional Neural Networks; Ensemble learning; Identification of fabric colors
https://www.sciencedirect.com/science/article/pii/S1568494622007360
no
7
info:eu-repo/semantics/article
262
Amelio, A.; Bonifazi, G.; Corradini, E.; Di Saverio, S.; Marchetti, M.; Ursino, D.; Virgili, L.
1 Contributo su Rivista::1.1 Articolo in rivista
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11564/799717
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