From 05a95d933f07a13536b037c9ef5bd9558c181f6f Mon Sep 17 00:00:00 2001 From: Benjamin Loison Date: Thu, 2 Oct 2025 16:46:17 +0200 Subject: [PATCH] Correct a typo in `README.md` Verified exhaustiveness thanks to: ```bash grep -rE ',[^ ]' --include=*.md ``` --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index f0b1ba2..70a756e 100644 --- a/README.md +++ b/README.md @@ -65,7 +65,7 @@ class PixelUnShuffle(Module): # Abstract Due to the fast inference and good performance, discriminative learning methods have been widely studied in image denoising. However, these methods mostly learn a specific model for each noise level, and require multiple models for denoising images with different noise levels. They also lack flexibility to deal with spatially variant noise, limiting their applications in practical denoising. To address these issues, we present a fast and flexible denoising convolutional neural network, namely FFDNet, with a tunable noise level map as the input. -The proposed FFDNet works on downsampled subimages,achieving a good trade-off between inference speed and +The proposed FFDNet works on downsampled subimages, achieving a good trade-off between inference speed and denoising performance. In contrast to the existing discriminative denoisers, FFDNet enjoys several desirable properties, including - the ability to handle a wide range of noise levels (i.e., [0, 75]) effectively with a single network,