Abstract. We present a framework for the automatic annotation of learning objects (LOs) with empirical usage metadata. Our implementation of the Intelligent Learning Object Guide (...
S. A. Riley, Lee Dee Miller, Leen-Kiat Soh, Ashok ...
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
We extend the standard mean-shift tracking algorithm to an adaptive tracker by selecting reliable features from color and shape-texture cues according to their descriptive ability....
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
In this paper, a novel feature selection algorithm for object tracking is proposed. This algorithm performs more robust than the previous works by taking the correlation between f...