Fourier-related Transforms
Discrete Cosine Transform
Discrete Cosine Transform (DCT) is an orthogonal transformation method that decomposes an image to its spatial frequency spectrum. It expresses a finite sequence of data points in terms of a sum of cosine functions oscillating at different frequencies. It is used a lot in compression tasks, e..g image compression where for example high-frequency components can be discarded. It is a type of Fourier-related Transform, similar to discrete fourier transforms (DFTs), but only using real numbers.
Image Credit: Wikipedia
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Image Compression | 16 | 6.15% |
| Quantization | 14 | 5.38% |
| Super-Resolution | 10 | 3.85% |
| General Classification | 10 | 3.85% |
| Image Classification | 9 | 3.46% |
| Decoder | 6 | 2.31% |
| Semantic Segmentation | 6 | 2.31% |
| Face Recognition | 6 | 2.31% |
| BIG-bench Machine Learning | 6 | 2.31% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
