 Research on the application of deep learning algorithm based PS design software technology in oil painting teachingXifeng Qin International Journal of Networking and Virtual Organisations, 2023, vol. 28, issue 2/3/4, 122-138 Abstract: More and more minors are cultivating oil painting as a hobby. Beginners of oil painting often cannot correctly identify optimised styles and similar painting objects due to the lack of professional knowledge and insufficient aesthetic ability of oil painting. This research addresses this problem by designing a shared convolutional neural network and an improved global convolutional neural network, and combining the two with Photoshop (short name: PS) software processing steps to compose an intelligent oil painting recognition model for beginner teaching. The experimental results of model performance testing show that the recognition model designed in this study has lower training and computation speed. However, the recognition accuracy of various images in the test sample set is higher than that of the comparison oil painting recognition model. Which is significantly higher than the oil painting recognition model built based on GoogleNet, visual geometry group (VGG) and AlexNet neural network algorithms. Keywords: deep learning; PS design software; oil painting teaching; convolutional neural network. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijnvor:v:28:y:2023:i:2/3/4:p:122-138 Access Statistics for this article More articles in International Journal of Networking and Virtual Organisations from Inderscience Enterprises Ltd |
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