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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Muhammad, Ismail | - |
| dc.contributor.author | Changjing, Shang | - |
| dc.contributor.author | Jing, Yang | - |
| dc.date.accessioned | 2023-03-31T07:16:48Z | - |
| dc.date.available | 2023-03-31T07:16:48Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.uri | https://link.springer.com/article/10.1007/s00521-021-06500-x | - |
| dc.identifier.uri | https://dlib.phenikaa-uni.edu.vn/handle/PNK/7385 | - |
| dc.description | CC BY | vi |
| dc.description.abstract | Image processing is a very broad field containing various areas, including image super-resolution (ISR) which re-represents a low-resolution image as a high-resolution one through a certain means of image transformation. The problem with most of the existing ISR methods is that they are devised for the condition in which sufficient training data is expected to be available. This article proposes a new approach for sparse data-based (rather than sufficient training data-based) ISR, by the use of an ANFIS (Adaptive Network-based Fuzzy Inference System) interpolation technique. | vi |
| dc.language.iso | en | vi |
| dc.publisher | Springer | vi |
| dc.subject | ISR | vi |
| dc.subject | ANFIS | vi |
| dc.title | Sparse data-based image super-resolution with ANFIS interpolation | vi |
| dc.type | Book | vi |
| Appears in Collections | OER - Công nghệ thông tin | |
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