Digital pathology and microscopy image analysis is widely used for comprehensive studies
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …

图像分割是指将图像分成若干具有相似性质的区域的过程, 是许多图像处理任务的预处理步骤.
近年来, 国内外学者主要研究基于图像内容的分割算法. 在广泛调研大量文献和最新成果的基础 …

Clustering for hyperspectral images (HSIs) is a very challenging task due to its inherent
complexity. In this paper, we propose a novel spectral-spatial sparse subspace clustering S …

In recent years, combining multiple sources or views of datasets for data clustering has been
a popular practice for improving clustering accuracy. As different views are different …

图像分割是指将图像分成若干具有相似性质的区域的过程, 是许多图像处理任务的预处理步骤.
近年来, 国内外学者主要研究基于图像内容的分割算法. 在广泛调研大量文献和最新成果的基础 …

The existing, semisupervised, spectral clustering approaches have two major drawbacks, ie,
either they cannot cope with multiple categories of supervision or they sometimes exhibit …

Reinforcement learning (RL) based traffic signal control for large-scale traffic grids is
challenging due to the curse of dimensionality. Most particularly, searching for an optimal …

Much work has been done in the field of texture analysis and classification. While promising
classification methods have been proposed, most of them rely on classical image analysis …

In recent decades, platinum-group metals have become increasingly important to the
development and diffusion of cleaner technologies being developed to achieve a “low …

Spectral clustering makes use of spectral-graph structure of an affinity matrix to partition data
into disjoint meaningful groups. It requires robust and appropriate affinity graphs as input in …