Methods › Computer Vision › Convolutional Neural Networks › Harm-Net
Harm-Net
Introduced by Matej Ulicny et al. in Harmonic Convolutional Networks based on Discrete Cosine Transform
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
A Harmonic Network, or Harm-Net, is a type of convolutional neural network that replaces convolutional layers with "harmonic blocks" that use Discrete Cosine Transform (DCT) filters. These blocks can be useful in truncating high-frequency information (possible due to the redundancies in the spectral domain).
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
-
Harmonic Convolutional Networks based on Discrete Cosine Transform 18 Jan 2020 · 1 repository · arXiv:2001.06570Syntology ran 0 of 10 samples · 10 unverified
Tasks archive 2025-07-28
6 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Edge Detection | 1 |
| Image Classification | 1 |
| Object Detection | 1 |
| Semantic Segmentation | 1 |
| image-classification | 1 |
| object-detection | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections