id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_72gex2yn5bfv5l3y3jhn3oamea	J. Kim	CLASSIFICATION OF OIL PAINTING USING MACHINE LEARNING WITH VISUALIZED DEPTH INFORMATION	2019	7	.pdf	application/pdf	5518	484	61	KEY WORDS: Machine Learning, Visualized Depth Information, RTI, Painting Analysis, Artist Classification In the past few decades, a number of scholars studied painting classification based on image processing or computer vision technologies. This study proposes a new data utilization approach in machine learning with Reflectance Transformation Imaging (RTI) images, which maximizes the visualization of a three-dimensional If these new types of images are applied as data to train in with the machine learning model, classification would In this paper, we propose a method which uses machine learning and RTI technology to analyze and classify paintings more We investigate three machine learning architecture for the painting classification task, which uses the RTI images as a training depth-visualized images improve the result of painting classification with machine learning, and in experiment 2, the number of training data was increased and the classification classes	./cache/work_72gex2yn5bfv5l3y3jhn3oamea.pdf	./txt/work_72gex2yn5bfv5l3y3jhn3oamea.txt