6 accepted papers
Tensor completion using multiway delay-embedding transform (MDT) (or Hankelization) suffers from the large memory requirement and high computational cost in spite of its high potentiality for the image modeling. Recent studies have shown high completion performance with a relatively small window siz…
Image segmentation is one of the most fundamental tasks in computer vision. In many practical applications, it is essential to properly evaluate the reliability of individual segmentation results. In this study, we propose a novel framework for quantifying the statistical significance of individual…
We propose a new method for cancer subtype classification from histopathological images, which can automatically detect tumor-specific features in a given whole slide image (WSI). The cancer subtype should be classified by referring to a WSI, i.e., a large-sized image (typically 40,000x40,000 pixels…
We propose a method that reconstructs dynamic positron emission tomography (PET) images from given sinograms by using non-negative matrix factorization (NMF) incorporated with a deep image prior (DIP) for appropriately constraining the spatial patterns of resultant images. The proposed method can re…
Let us consider a case where all of the elements in some continuous slices are missing in tensor data. In this case, the nuclear-norm and total variation regularization methods usually fail to recover the missing elements. The key problem is capturing some delay/shift-invariant structure. In this…
Tensor completion has attracted attention because of its promising ability and generality. However, there are few studies on noisy scenarios which directly solve an optimization problem consisting of a "noise inequality constraint". In this paper, we propose a new tensor completion and denoising m…