| Autor: |
Zhu Xiaohong |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2444-8656 |
| DOI: |
10.2478/amns.2023.2.00858 |
| Popis: |
In this paper, we propose a deep learning restoration method for fine art painting images based on a contextual encoder and select a convolutional self-encoder-based image restoration model for workflow analysis, including forward inference and backward network propagation. We design and develop a software system for predicting the grades of college art and painting students and apply the neural network prediction model to this system to realize the grade prediction of college art students. The accuracy of the GDPN model is 0.922, the precision is 0.904, and the recall is 0.966, which can consider both the temporal and overall information in the click behavior and achieve a better prediction effect. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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