With the increase in the usage of the Internet, a large amount of information is exchanged
between different communicating devices. The data should be communicated securely …

Selecting relevant feature subsets is vital in machine learning, and multiclass feature
selection is harder to perform since most classifications are binary. The feature selection …

Unsupervised feature selection attempts to select a small number of discriminative features
from original high-dimensional data and preserve the intrinsic data structure without using …

随着模式识别, 机器学习, 遥感技术等相关学科领域的发展, 高光谱遥感影像分类研究取得快速
进展. 本文系统总结和评述了当前高光谱遥感影像分类的相关研究进展, 在总结分类策略的基础 …

摘要视觉跟踪问题是当前计算机视觉领域中的热点问题, 本文对这一问题进行了详细的介绍.
首先, 对视觉跟踪技术在视频监视, 图像压缩和三维重构等三个主要方面的应用进行了论述 …

Safety and reliability are absolutely important for modern sophisticated systems and
technologies. Therefore, malfunction monitoring capabilities are instilled in the system for …

High-dimensional data analysis is a challenge for researchers and engineers in the fields of
machine learning and data mining. Feature selection provides an effective way to solve this …

Nowadays, being in digital era the data generated by various applications are increasing
drastically both row-wise and column wise; this creates a bottleneck for analytics and also …

In recent years, unsupervised feature selection methods have raised considerable interest in
many research areas; this is mainly due to their ability to identify and select relevant features …

Leaf chlorophyll, as a key factor for carbon circulation in the ecosystem, is significant for the
photosynthetic productivity estimation and crop growth monitoring in agricultural …