Name
Abstract | ||
|---|---|---|
•A dynamic convolution is used into a CNN to address limitations in depth and width of lightweight CNNs for pursuing good denoising performance.•The combination of a signal processing technique and discriminative learning technique is used for image denoising.•Enhanced residual dense architectures are used to remove redundant information for improving denoising effects. |
Year | DOI | Venue |
|---|---|---|
2023 | 10.1016/j.patcog.2022.109050 | Pattern Recognition |
Keywords | DocType | Volume |
Image denoising,CNN,Wavelet transform,Dynamic convolution,Signal processing | Journal | 134 |
Issue | ISSN | Citations |
1 | 0031-3203 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chunwei Tian | 1 | 134 | 9.42 |
| Menghua Zheng | 2 | 0 | 0.34 |
| Wangmeng Zuo | 3 | 3833 | 173.11 |
| Bob Zhang | 4 | 728 | 69.17 |
| Yanning Zhang | 5 | 1613 | 176.32 |
| David Zhang | 6 | 2337 | 102.40 |