We introduce a flexible technique for interactive exploration of vector field data through classification derived from user-specified feature templates. Our method is founded on the observation that, while similar features ...

Functional Data Analysis (FDA) has become a very important eld in recent years due to its wide range of applications. However, there are several real-life applications in which hybrid functional data appear, i.e., data ...

Abstract. State of the Art language identification methods are based on acoustic or phonetic features. Recently, phono-articulatory features have been included as a new speech characteristic that conveys language ...

This work proposes two new techniques of feature vector pre-processing to improve CBIR and image classification systems: a method of feature transformation based on the k-means clustering approach (Feature Transformation ...

This paper presents a human detection system based on component detector using multiple feature descriptors. The contribution presents two issues for dealing with the problem of partially obscured human. First, it presents ...

The efficiency in image classification tasks can be improved using combined information provided by several sources, such as shape, color, and texture visual properties. Although many works proposed to combine different ...

The efficiency in image classification tasks can be improved using combined information provided by several sources, such as shape, color, and texture visual properties. Although many works proposed to combine different ...

The performance of classification methods, such as Support Vector Machines, depends heavily on the proper choice of the feature set used to construct the classifier. Feature selection is an NP-hard problem that has been ...

Churn prediction is an important application of classification models that identify those customers most likely to attrite based on their respective characteristics described by e.g. socio-demographic and behavioral ...