Abstract
Presence of noise poses a common problem in image recognition tasks. In this paper we propose and analyse architecture of convolutional neural network capable of image denoising. We evaluate its performance with various types of artificial distortions present, with both known and unknown noise conditions. Finally, we measure how including denoising procedure in image recognition pipeline influences classification accuracy.
Cite
CITATION STYLE
Koziarski, M., & Cyganek, B. (2016). Deep neural image denoising. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9972 LNCS, pp. 163–173). Springer Verlag. https://doi.org/10.1007/978-3-319-46418-3_15
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