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A robust classifier combined with an auto-associative network for completing partly occluded images
2005
Neural Networks
This paper describes an approach for constructing a classifier which is unaffected by occlusions in images. We propose a method for integrating an auto-associative network into a simple classifier. As the auto-associative network can recall the original image from a partly occluded input image, we can employ it to detect occluded regions and complete the input image by replacing those regions with recalled pixels. By iterating this reconstruction process, the integrated network is able to
doi:10.1016/j.neunet.2005.03.011
pmid:15936926
fatcat:jebyvkxm4vhs5lon66vzfy2tse