In this paper, we propose an object detection approach using spatial histogram features. As spatial histograms consist of marginal distributions of an image over local patches, they can preserve texture and shape information of an object simultaneously. We employ Fisher criterion and mutual information to measure discriminability and features correlation of spatial histogram features. We furthe...

A voice quality prediction method based on Gaussian mixture models (GMMs) is improved by constructing a feature selection algorithm to provide the best GMMbased prediction quality. The proposed sequential selection algorithm performs N -survivor search, allowing for trading between design complexity and performance. Simulation shows that predictors designed using the proposed algorithm outperfo...

This paper describes an automatic feature selection algorithm integrated into a classification framework developed to discriminate between sleep and wake states during the night. The feature selection algorithm proposed in this paper uses the Mahalanobis distance and the Spearman’s ranked-order correlation as selection criteria to restrict search in a large feature space. The algorithm was test...

This work tackles the problem of selecting a subset of features in an inductive learning setting, by introducing a novel Thermodynamic Feature Selection algorithm (TFS). Given a suitable objective function, the algorithm makes uses of a specially designed form of simulated annealing to find a subset of attributes that maximizes the objective function. The new algorithm is evaluated against one ...

Software cost estimation is one of the most crucial processes in software development management because it involves many management activities such as project planning, resource allocation and risk assessment. Accurate software cost estimation not only does help to make investment and bid plan but also enable the project to be completed in the limited cost and time. The research interest of th...