Machine Learning and Data Mining research strongly depend on the quality and quantity of the real world datasets for the evaluation stages of the developing methods. In the context of the emerging Online Multi-Target Regression and Multi-Label Classification methodologies, datasets present new characteristics that require specific testing and represent new challenges. The first difficulty found...

There are several publications dedicated to the description and analysis of change detection between two gray-value images. This paper now introduces new methods to detect moving objects between multiple images and to detect changes between color images or any type of multispectral images. We are not aware of methods giving the possibility to detect color changes and changes between multiple fr...

Work described in this paper is aimed at developing a monitoring and fault detection system for the process plant. In particular this work concentrates on how to combine qualitative reasoning techniques with conventional numerical sensor fusion techniques. The advantages and disadvantages of using pure numerical or pure qualitative technique alone arefirst demonstrated. A method of developing a...

For the anomalous change detection problem, you have a pair of images, taken of the same scene, but at different times and typically under different viewing conditions. You are looking for interesting differences between the two images. There will be some differences that are pervasive, perhaps due to overall contrast, brightness or focus differences, or maybe due to atmospheric or even seasona...

A large number of shot boundary detection, or equivalently, transition detection techniques have been developed in recent years. The shot boundary detection includes abrupt and gradual shot change detection. Gradual shot change detection is more challenging task than abrupt shot change detection. Thus aim of this paper is mainly to focus on gradual boundary detection. Previous researches relate...

We address the problem of detecting ‘‘anomalies’’ in the network traffic produced by a large population of end-users following a distribution-based change detection approach. In the considered scenario, different traffic variables are monitored at different levels of temporal aggregation (timescales), resulting in a grid of variable/timescale nodes. For every node, a set of per-user traffic cou...

This article presents a Radial Basis Neural Network (RBNN) based islanding detection technique. Islanding detection and prevention is a mandatory requirement for grid-connected distributed generation (DG) systems. Several methods based on passive and active detection scheme have been proposed. While passive schemes have a large non detection zone (NDZ), concern has been raised on active method ...