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
Paper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Image Compression | 14 | 6.90% |
Quantization | 12 | 5.91% |
General Classification | 10 | 4.93% |
Super-Resolution | 8 | 3.94% |
Image Classification | 6 | 2.96% |
Face Recognition | 6 | 2.96% |
BIG-bench Machine Learning | 6 | 2.96% |
Decoder | 4 | 1.97% |
Data Compression | 4 | 1.97% |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |