Browsing by Subject "Classification approach"

Now showing 1 - 4 of 4

Open Access
Machine-based learning system: classification of ADHD and non-ADHD participants
(IEEE, 2017) Öztoprak, H.; Toycan, M.; Alp, Y. K.; Arıkan, Orhan; Doğutepe, E.; Karakaş, S.
Attention-deficit/hyperactivity disorder (ADHD) is the most frequent diagnosis among children who are referred to psychiatry departments. Although ADHD was discovered at the beginning of the 20th century, its diagnosis is confronted with many problems. In this paper, a novel classification approach that discriminates ADHD and non-ADHD groups over the time-frequency domain features of ERP recordings is presented. Support Vector Machine-Recursive Feature Elimination (SVM-RFE) was used to obtain best discriminating features. When only three of these features were used the accuracy of classification reached to 98%, and use of six features further improved classification accuracy to 99.5%. The proposed scheme was tested with a new experimental setup and 100% accuracy is obtained. The results were obtained using RCV. The classification performance of this study suggests that TFHA can be employed as a core component of the diagnostic and prognostic procedures of various psychiatric illnesses.
Open Access
Multidimensional classification approach for defining product line engineering transition strategies
(Springer, Berlin, Heidelberg, 2010) Tekinerdoğan, Bedir; Tüzün, E.; Şaykol, E.
It is generally acknowledged that the transitioning process to a product line engineering approach is not trivial and as such requires a planned transition process. Different classifications of transition strategies have been proposed in the literature. It appears that these classification schemes are usually based on a single dimension. However, the adoption of a transition strategy is dependent on various criteria and very often it is not easy to characterize the required transition strategy. An appropriate characterization of the transition strategy is important for carrying out the right transition activities and steps to provide an operational product line engineering approach. In this paper, we first provide a conceptual model for defining the concepts related to transition strategies and then propose a multi-dimensional classification approach that aims to provide a more complete view on transition strategies. © 2010 Springer-Verlag Berlin Heidelberg.
Open Access
Rapid classification of surface reflectance from image velocities
(Springer, Berlin, Heidelberg, 2009) Doerschner, Katja; Kersten, D.; Schrater P.
We propose a method for rapidly classifying surface reflectance directly from the output of spatio-temporal filters applied to an image sequence of rotating objects. Using image data from only a single frame, we compute histograms of image velocities and classify these as being generated by a specular or a diffusely reflecting object. Exploiting characteristics of material-specific image velocities we show that our classification approach can predict the reflectance of novel 3D objects, as well as human perception. © 2009 Springer Berlin Heidelberg.
Open Access
Subset selection with structured dictionaries in classification
(EURASIP, 2007) İnce, N. F.; Göksu, F.; Tewfik, A. H.; Onaran, İbrahim; Çetin, A. Enis
This paper describes a new approach for the selection of discriminant time-frequency features for classification. Unlike previous approaches that use the individual discrimination power of expansion coefficients, the proposed approach selects a subset of features by implementing a classifier directed pruning of an initial redundant set of candidate features. The candidate features are calculated from a structured redundant time-frequency analysis of the signal, such as an undecimated wavelet transform. We show that the proposed approach has a performance that is as good as or better than traditional classification approaches while using a much smaller number of features. In particular, we provide experimental results to demonstrate the superior performance of the algorithm in the area of impact acoustic classification for food kernel inspection. The proposed algorithm achieved 91.8% and 98.5% classification accuracies in separating open shell from closed shell pistachio nuts and discriminating between empty and full hazelnuts respectively. Traditional methods used in this area resulted in 82% and 97% classification accuracies respectively.