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Apr, 2018
嵌入空间低秩模型的张量缺失切片恢复
Missing Slice Recovery for Tensors Using a Low-rank Model in Embedded Space
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Tatsuya Yokota, Burak Erem, Seyhmus Guler, Simon K. Warfield, Hidekata Hontani
TL;DR
本研究提出了一种用于多维张量数据的低秩模型和一种基于Tucker分解的低秩张量分解方法，该方法能够成功地恢复一些彩色图像和功能磁共振成像中的丢失部分。
Abstract
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 v
→