In the diagnosis of epileptic seizures, classification is an important step that directly affects results. Visual inspection Electroencephalogram (EEG) a relatively common analytic method epilepsy, but it costly, time-consuming and relies on experiences doctor. Therefore, development efficient accurate seizure automatic system suitable for clinical has become urgent task. order to better solve ...

The more tourist objects are in an area, the challenging it is for local governments to increase selling value of these attractions. government always strives develop attraction areas by prioritizing beauty However, visitors often have difficulty determining that match their criteria because many choices. research developed a recommendation system applying machine learning techniques. technique...

human action recognition is an important problem in computer vision. one of the methods that are recently used is sparse coding. conventional sparse coding algorithms learn dictionaries and codes in an unsupervised manner and neglect class information that is available in the training set. but in this paper for solving this problem, we use a discriminative sparse code based on multi-manifolds. ...

k-nearest neighbors (k-NN), which is known to be a simple and efficient approach, is a non-parametric supervised classifier. It aims to determine the class label of an unknown sample by its k-nearest neighbors that are stored in a training set. The k-nearest neighbors are determined based on some distance functions. Although k-NN produces successful results, there have been some extensions for ...

In this paper, we propose a new matting algorithm using local and nonlocal neighbors. We assume that K nearest neighbors satisfy the color line model that RGB distribution of the neighbors is roughly linear and combine this assumption with the local color line model that RGB distribution of local neighbors is roughly linear. Our assumptions are appropriate for various regions such as those that...

The k-nearest neighbor rule is one of the simplest and most attractive pattern classification algorithms. It can be interpreted as an empirical Bayes classifier based on the estimated a posteriori probabilities from the k nearest neighbors. The performance of the k-nearest neighbor rule relies on the locally constant a posteriori probability assumption. This assumption, however, becomes problem...

Photon mapping is one of the most important algorithms for computing global illumination. Especially for efficiently producing convincing caustics, there are no real alternatives to photon mapping. On the other hand, photon mapping is also quite costly: Each radiance lookup requires to find the k nearest neighbors in a kd-tree, which can be more costly than shooting several rays. Therefore, the...