U-SRN: Convolutional Neural network for single image super resolution
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-17379-2.pdf
Reference49 articles.
1. Cheng Y, Ling K, Lin Y (2023) Image super resolution via combination of two dimensional quaternion valued singular spectrum analysis based denoising, empirical mode decomposition based denoising and discrete cosine transform based denoising methods. Multimed Tools Appl. https://doi.org/10.1007/s11042-023-14474-2
2. Iqbal M, Riaz MM, Ghafoor A (2021) Kernel estimation and optimization for image de-blurring using mask construction and super-resolution. Multimed Tools Appl 80:10361–10372
3. Srinivas G, Naga Srinivasu P, Srinivas Rao T, Ramesh C (2018) Harmonic and Contra-Harmonic Mean-Centric JPEG Compression for an Objective Image Quality Enhancement of Noisy Images. Smart Comput Inform Smart Innov, Syst Technol, Springer 78:143–152. https://doi.org/10.1007/978-981-10-5547-8_14
4. Naga Srinivasu P, Balas VE, Md. Norwawi N (2021). Performance Measurement of Various Hybridized Kernels for Noise Normalization and Enhancement in High-Resolution MR Images. Bio-inspired Neurocomputing. Stud Comput Intell Springer, Singapore, 903, pp.1-24. https://doi.org/10.1007/978-981-15-5495-7_1
5. Bisen D, Shukla R, Rajpoot N (2022) Responsive human-computer interaction model based on recognition of facial landmarks using machine learning algorithms. Multimed Tools Appl 81:18011–18031
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