This paper presents a feasibility study of evolutionary scheduling for gas pipeline operations. The problem is complex because of several constraints that must be taken into consi...
This paper presents a novel approach to pedestrian classification which involves utilizing the synthesized virtual samples of a learned generative model to enhance the classificat...
Abstract— Meta-Learning has been used to predict the performance of learning algorithms based on descriptive features of the learning problems. Each training example in this cont...
We investigate how it is possible to shape robot behaviour adopting a molecular or molar point of view. These two ways to approach the issue are inspired by Learning Psychology, wh...
Content-based classification of audio data is an important problem for various applications such as overall analysis of audio-visual streams, boundary detection of video story se...