CUP- Convolutional Neural Network Training dataset

Published: 23 April 2024| Version 3 | DOI: 10.17632/7md9bgd4tg.3
taraneh saniei


The dataset has been provided for training a convolutional neural network to measure some selected visual design principles. These visual principles are related to the preference matrix which is adopted from Kaplan and Kaplan (1989). The dataset is contained of images that illustrate the considered variables as obviously as possible and the CNN trained by them can be used for analysis in fields of art and architecture. CUP is the short form of contrast, unity, and proportion. 3 types of complementary color contrasts, 2 types of warm/cold contrasts, light/dark contrast, similarity in color and variety in form , proportion and similarity in form and variety in color. The dataset is a collection of images found in the search through google and pinterest, and some of them may be subject to copyright. For such images, the copyright of all the images belongs to the image owners.



Visual Arts, Visual Analytics, Architectural Design, Deep Learning, Interior Design