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We propose a learning algorithm using multiple eigen subspaces to handle sudden illumination variations in background subtraction. The feature space is organized into clusters representing the different lighting conditions. A Local Principle Component Analysis (LPCA) transformation is used to...
Evolving Takagi Sugeno (eTS) models are optimised for use in applications with high sampling rates. This mode of use produces excellent prediction results very quickly and with low memory requirements, even with large numbers of input attributes. In this paper eTS modelling is adapted for...
The paper contains a description of the implementation and performance evaluation of the agent-based population learning algorithm used to train the feed-forward artificial neural networks. The goal of the research was to evaluate efficiency of the agent-based approach and to establish...
The task scheduling problem in heterogeneous systems (TSPHS) is a NP-complete problem. It is a multiobjective optimization problem (MOP). The objectives such as makespan, average flow time, robustness and reliability of the schedule are considered for solving task scheduling problem. This paper...
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