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Impact of Image Degradation on CNNs by extras.storage1 is a document available to read on EtoBox.
What is Impact of Image Degradation on CNNs about?
This paper investigates the impact of various types of image degradation on the performance of CNN-based image classification. It empirically studies nine kinds of degraded images, including hazy, motion-blurred, and low-resolution images, to determine whether degradation removal can enhance classification accuracy. The findings aim to encourage further research into the classification of degraded images within the computer vision community.
- Author
- extras.storage1
- Language
- EN