The proposed method is to recognize objects based on application of Local Steering Kernels (LSK) as Descriptors to the image patches. In order to represent the local properties of the images, patch is to be extracted where the variations occur in an image. To find the interest point, Wavelet based Salient Point detector is used. Local Steering Kernel is then applied to the resultant pixels, in ...

in this paper, a robust integral of the sign error (rise) feedback controller is designed for a rigid-link electrically driven (rled) robot manipulator actuated by direct current dc motor in presence of parametric uncertainties and additive disturbances. rise feedback with implicitly learning capability is a continuous control method based on the lyapunov stability analysis to compensate an add...

support vector machine (svm) was used to analyze the occurrence of roach in flemish stream basins (belgium). several habitat and physico?chemical variables were used as inputs for the model development. the biotic variable merely consisted of abundance data which was used for predicting presence/absence of roach. genetic algorithm (ga) was combined with svm in order to select the most important...

the lithologies of regions, which located near the collision zone, are very different from other geology setting. mapping in these areas needs extensive and exact studies and tools because of the variety of rocks, intensive tectonic uplift and complicated units. hyperspectral sensor is one of the most advanced tools with hundreds of bands that each measures a very narrow range of wavelengths an...

background: we aimed to assess the high-risk group for suicide using different classification methods includinglogistic regression (lr), decision tree (dt), artificial neural network (ann), and support vector machine (svm). methods: we used the dataset of a study conducted to predict risk factors of completed suicide in hamadan province, the west of iran, in 2010. to evaluate the high-risk grou...

In this paper, several neural network and statistical learning approaches are proposed that learn to make human like decisions for the job assignment problem of the US Navy. Comparison study of Feedforward Neural Networks (FFNN), Adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM) and Adaptive Bayes (AB) classifier with Generalized Estimation Equation (GEE) is provided. ...

A classification technique using Support Vector Machine (SVM) classifier for detection of rolling element bearing fault is presented here.  The SVM was fed from features that were extracted from of vibration signals obtained from experimental setup consisting of rotating driveline that was mounted on rolling element bearings which were run in normal and with artificially faults induced conditio...

Automatic signal type identification (ASTI) is an important topic for both the civilian and military domains. Most of the proposed identifiers can only recognize a few types of digital signal and usually need high levels of SNRs. This paper presents a new high efficient technique that includes a variety of digital signal types. In this technique, a combination of higher order moments and hi...

In this paper, several two-dimensional extensions of principal component analysis (PCA) and linear discriminant analysis (LDA) techniques has been applied in a lossless dimensionality reduction framework, for face recognition application. In this framework, the benefits of dimensionality reduction were used to improve the performance of its predictive model, which was a support vector machine (...

Background: Migraine headache without aura is the most common type of migraine especially among pediatric patients. It has always been a great challenge of migraine diagnosis using quantitative electroencephalography measurements through feature classification. It has been proven that different feature extraction and classification methods vary in terms of performance regarding detection and di...