Research on Image Super Resolution Reconstruction Model Based on Deep Learning. Issue 3 (October 2020)

• Record Type: Journal Article
• Authors: Zeng, Yuhao; Peng, Sijie; Ruan, Shengyi
• Is Part Of: Journal of physics. Volume 1650:Issue 3(2020)
• Publication Date: 2020-10
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1650/3/032129
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Artificial neural network has made the rapid development of artificial intelligence with its super-learning ability, making artificial neural network become a research hotspot again. At present, deep learning has been widely used in various fields such as computer vision, speech processing, and natural language processing, and has even played a leading role in some fields. The single image super-resolution reconstruction technique aims to reconstruct a low-resolution image through a series of algorithms to reconstruct a corresponding high-resolution image. This paper first briefly introduces the relevant theories of artificial neural networks, then studies the fast super-resolution reconstruction model, and improves the model layer and filter size to establish a new improved model.