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## ひとことで表すと
人間の視覚にはshape-biasがあることに着目し、モデルにShape-biasをかける手法を提案。これにより、画像のスタイル変換・ノイズ・AEに対するモデルのロバスト性の向上を目的とした。Robustnessの観点で、Shape-biasに着目した初の論文。
手法としては、新たなDropOutレイヤーを提案した。"InfoDrop"とよぶ。
## 論文リンク
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🚨Please review the [Troubleshooting](../#troubleshooting) section
before reporting any issue. Don't forget to check also the current issues to
avoid duplicates.
### Subject of the issue
Describe…
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## Why
Machine Learning 輪講は最新の技術や論文を追うことで、エンジニアが「技術で解決できること」のレベルをあげていくことを目的にした会です。
prev. #33
## What
話したいことがある人はここにコメントしましょう！
面白いものを見つけた時点でとりあえず話すという宣言だけでもしましょう！
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Great paper Andrew!!
Out of curiosity , how do you come up w/ the choice of modulo polynomials? Trial & error to figure out polynomial which'd give the minimal muls?
For cyclic convolutions, it's …
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Similar to benchmarks created for image classification, we would like to create a benchmark for video datasets.
A few tasks for tackling video datasets:
1. Identify ML training related to video …
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Networks composed of tanh, sigmoid, etc. and general nonlinear activations
Representative benchmark(s): control theory controllers
Questions: allow or disallow other nonlinearities as a sort of …
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### Is there an existing issue for this?
- [X] I have searched the existing issues
### Feature Description
This project implements Neural Style Transfer (NST), a deep learning technique that applie…
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When I test on consistent medical images, although some images are very similar to each other, their detection results are different. I set thresh 0.5.
![image](https://user-images.githubusercontent…
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Thank you for your work!
Could you please provide guidance on how to properly cite this work? Additionally, what Creative Commons license applies to the datasets provided?
Thanks!
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