@inbook{8d883f1ad7564677b5fab6b25e4b1fd6,
title = "Style Painting Classifier Based on Horn Clauses and Explanations (SHE)",
abstract = "This paper presents an style painting classifier, based on Horn clauses in rational Pavelka logic and qualitative colour descriptors, that provides explanations (SHE). A fuzzy representation of colour traits for Baroque, Impressionism and Post-Impressionism art styles is introduced. The SHE-algorithm has been implemented in Swi-Prolog and tested on the 90 paintings in QArt-Dataset. the Baroque style was classified in 90% of accuracy. The general accuracy for all the art styles was 73.3%. SHE provided explanations of right classifications, and also of outliers by giving a second option depending on the membership degree of the painting to a certain style.",
keywords = "art, classifier, explainable AI, Horn clause, logic programming, qualitative colour",
author = "Vicent Costa and Pilar Dellunde and Zoe Falomir",
note = "Publisher Copyright: {\textcopyright} 2018 The authors and IOS Press.",
year = "2018",
doi = "10.3233/978-1-61499-918-8-37",
language = "English",
isbn = "9781614999171",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press",
pages = "37--46",
editor = "Karina Gibert and Zoe Falomir and Enric Plaza",
booktitle = "Artificial Intelligence Research and Development",
address = "United States",
}