CUP- Convolutional Neural Network Training dataset

Published: 28 November 2022| Version 1 | DOI: 10.17632/7md9bgd4tg.1
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 images that illustrate considered variables as obviously as possible and the CNN trained by them can be used for analogies in fields of art and architecture. CUP is the short form of contrast, unity, and proportion. 3 kinds of complementary color contrasts, 2 kinds of warm/cold contrasts, light/dark contrast, similarity in color and variety in form(for 3 main colors), proportion and similarity in form and variety in color.



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