The research reported in this paper is concerned with assessing the usefulness of reinforcment learning (RL) for on-line calibration of parameters in evolutionary algorithms (EA). ...
A. E. Eiben, Mark Horvath, Wojtek Kowalczyk, Marti...
Learning vector quantization (LVQ) constitutes a powerful and intuitive method for adaptive nearest prototype classification. However, original LVQ has been introduced based on he...
We have proposed a complete system for text detection and localization in gray scale scene images. A boosting framework integrating feature and weak classifier selection based on...
In this paper, a neuro-fuzzy algorithm has been implemented to improve the path planning of a mobile robot based on modification of vector field histogram (VFH) approach using neu...
Backpropagation of errors is not only hard to justify from biological perspective but also it fails to solve problems requiring complex logic. A simpler algorithm based on generati...