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Classification for degraded images having various levels of degradation isvery important in practical applications. This paper proposes a convolutionalneural network to classify degraded images by using a restoration network andan ensemble learning. The results demonstrate that the proposed network canclassify degraded images over various levels of degradation well. This paperalso reveals how the image-quality of training data for a classificationnetwork affects the classification performance of degraded images.

Classifying degraded images over various levels of degradation