Koraljka Golub, Pawel Michal Ziolkowski and Goran Zlodi. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Joan M. Benedetti, Words, Words, Words: Folk Art Terminology—Why It (Still) Matters, Art Documentation: Journal of the Art Libraries Society of North America, Vol. 19, No. 1 (Spring 2000), pp. 14-21
Janet L. Stanley, AFRICAN ART AND AAT, Art Documentation: Journal of the Art Libraries Society of North America, Vol. 4, No. 3 (Fall 1985), pp. 103-105
Alison Gilchrest, Factors Affecting Controlled Vocabulary Usage in Art Museum Information Systems, Art Documentation: Journal of the Art Libraries Society of North America, Vol. 22, No. 1 (Spring 2003), pp. 13-20
Purpose: Based on the highlights of The Metropolitan Museum of Art's collection, the purpose of this paper is to examine the similarities and differences between the subject keywords tags assigned by the museum and those produced by three computer vision systems. Design/methodology/approach: This paper uses computer vision tools to generate the data and the Getty Research Institute's Art and Architecture Thesaurus (AAT) to compare the subject keyword tags. Findings: This paper finds that there are clear opportunities to use computer vision technologies to automatically generate tags that expand the terms used by the museum. This brings a new perspective to the collection that is different from the traditional art historical one. However, the study also surfaces challenges about the accuracy and lack of context within the computer vision results. Practical implications: This finding has important implications on how these machine-generated tags complement the current taxonomies and vocabularies inputted in the collection database. In consequence, the museum needs to consider the selection process for choosing which computer vision system to apply to their collection. Furthermore, they also need to think critically about the kind of tags they wish to use, such as colors, materials or objects. Originality/value: The study results add to the rapidly evolving field of computer vision within the art information context and provide recommendations of aspects to consider before selecting and implementing these technologies...
5.js is a friendly tool for learning to code and make art. It is a free and open-source JavaScript library built by an inclusive, nurturing community. p5.js welcomes artists, designers, beginners, educators, and anyone else!
SN Bollywood makeup academy is the best nail extention training academy. We offer the most creative, stylish nail extention and nail art training in Delhi, India.