This paper presents a weighted support vector machine (WSVM) to improve the outlier sensitivity problem of standard support vector machine (SVM) for two-class data classification. The basic idea is to assign different weights to different data points such that the WSVM training algorithm learns the decision surface according to the relative importance of data points in the training data set. Th...

As the basic unit of farmland, parcel is crucial for remote sensing tasks, such as urban management. Previous studies farmland parcels extraction are based on boundary detection and instance segmentation methods. However, these methods perform poorly in with complex shape fuzzy due to insufficient feature capability. Moreover, lack multi-scale features fusion, they difficult extract different s...

Recently, the application of the conventional rule based expert system for disease risk determination in medical domains has increased. However, a major limitation to the effectiveness of the rule based expert system approach is the sharp boundary problem that leads to underestimation or overestimation of boundary cases, which ultimately affects the accuracy of their recommendation. In this pap...

Face and hand tracking are important areas of research, related to adaptive human-computer interfaces, and affective computing. In this article we have introduced two new methods for boundary detection of the human face in video sequences: (1) edge density thresholding, and (2) fuzzy edge density. We have analyzed these algorithms based on two main factors: convergence speed and stability again...

Sliding control guarantees system performance in the presence of modeling uncertainties and parameter inaccuracies. However this is obtained at the price of high control activity that may exacerbate chattering. As one way to alleviate this problem a continuation method using boundary layer around switching is usually used. In this case selecting the control bandwidth and boundary layer thicknes...

Due to the complexities of objects and the vagueness of the human mind, it has attracted considerable attention from researchers studying fuzzy classification algorithms. In this paper, we propose a concept of fuzzy relative entropy to measure the divergence between two fuzzy sets. Applying fuzzy relative entropy, we prove the conclusion that patterns with high fuzziness are close to the classi...

In this paper, a fuzzy-neural adaptive iterative learning control (AILC) is proposed for traffic flow systems of a single lane freeway with random bounded off-ramp traffic volumes. It is assumed that the system dynamic functions and input gains are unknown for controller design. An adaptive fuzzy neural network (FNN) controller and an adaptive robust controller are applied to compensate for the...

In general, road lane detection from a traffic surveillance camera is done by the analysis of geometric shapes of the road. Thus, Hough transform or B-snake technology is preferred to intelligent pattern matching or machine learning such as neural network. However, we insist that the feasibility of using intelligent technique in this area is quite undervalued. In this paper, we first divide the...

In this paper, we present a combined approach designed for automated segmentation of radiological image, such as CT, MRI, etc, to get the organ or interested area from the image. This approach integrates region-based method and boundary-based method. Such integration reduces the drawbacks of both methods and enlarges the advantages of them. Firstly, we use fuzzy connectedness method to get an i...

Edge is the boundary between an object and the background, and identifies the boundary between overlapping and non-over lapping objects. This means that if the edges in an image can be identified accurately, all of the objects can be located and basic properties such as area, perimeter, and shape can be measured. Here fuzzy logic based image processing is used for accurate and noise free edge d...