Rough-set based multimodal histogram thresholding technique is effective for medical
image segmentation. However, it is difficult to obtain the significant peaks and valleys of the …

In this paper we consider the problem of detecting binary objects using rough sets. We
present a method for constructing a gray-scaled (or, fuzzy) template for use in correlation …

This paper proposes an integrated intelligent system that builds a fault diagnosis inference
model based on the advantage of rough set theory and genetic algorithms (GAs). Rough set …

In recent years, the rough set (RS) method has been in common use for remote-sensing
classification, which provides one of the techniques of information extraction for Digital …

In this paper, a new method is described to construct rough neural networks. On the base of
rough set model, we present a method to develop rough neural network of variable precision …

Data mining methods have been widely applied on the area of remote sensing classification
in recent years. In these methods, neural network, rough sets and support vector machine …

Our research group built a super-low altitude detection platform with power delta wings and
mounted it with a HySpex hyperspectral sensor. This platform has great potential for …

This paper proposes a more effective supervised classification algorithm of remote sensing
satellite image that uses the average fuzzy intracluster distance within the Bayesian …

本文研究了基于变精度粗糙集模型下的粗集神经网络设计, 对β **似约简条件进行了弱化推广,
同时提出了β **似约简的选取原则. 在对Brodatz 纹理图像的分类实验中, 比较了经典粗集神经 …

Based on bottom-up fuzzy rough data analysis, a new rough neural network decision-
making model is proposed. Through supervised Gaustafason–Kessel (G–K) clustering …