Text Classification Techniques: A Literature Review Page 1 Volume 13, 2018 Accepted by
Editor Maureen Tanner│ Received: July 7 3, 2017│ Revised: October 31, 2017, January …

Remote sensing images are featured by massiveness, diversity and complexity. These
features put forward higher requirements for the speed and accuracy of remote sensing …

In this paper, a novel model named projection-preserving block-diagonal low-rank
representation (PBDIR) is proposed and can obtain a more distinguishable representation …

Inspired by the temporal subspace clustering (TSC) method and low-rank matrix
approximation constraint, a new model is proposed termed as temporal plus low-rank …

Deep subspace learning is an important branch of self-supervised learning and has been a
hot research topic in recent years, but current methods do not fully consider the …

Sequential data clustering is a challenging task in data mining (eg, motion recognition and
video segmentation). For good performance in dealing with complex local correlation and …

Subspace clustering has long been recognized as vulnerable toward gross corruptions--the
corruptions can easily mislead the estimation of the underlying subspace structure …

Abstract Huaihe River Basin (HRB) is located in China's north-south climatic transition zone,
which is very sensitive to global climate change. Based on the daily maximum temperature …

Sequential data clustering plays an important role in many applications, such as motion
recognition, video segmentation, gene sequence analysis, and so on. The key idea is to …

Soil temperature (Ts), a key variable in geosciences study, has generated growing interest
among researchers. There are many factors affecting the spatiotemporal variation of Ts …