WaveCNet : Wavelet Integrated CNNs to Suppress Aliasing Effect for Noise-Robust Image Classification
Though widely used in image classification, convolutional neural networks (CNNs) are prone to noise interruptions, i.e. the CNN output can be drastically changed by small image noise. To improve the noise robustness, we try to integrate CNNs with wavelet by replacing the common down-sampling (max-po...
Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 30(2021) vom: 01., Seite 7074-7089 |
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Format: | Online-Aufsatz |
Sprache: | English |
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2021
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Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
Schlagworte: | Journal Article |
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