Educators and psychologists have debated on the efficacy of personalizing teaching methods according to learning style [1-3]. Recently, the styles are obtained from learning models, and it has been shown that utilizing those styles leverages educational effect. However, the researcher uses only two features which are the classification accuracy of human and response time, and it has been sugges...

Fishery video data often require laborious visual analysis, therefore a video-based fish identification challenge is announced in the LifeCLEF campaign for automatic fish categorization and enumeration. We have elaborated a complex system to detect, classify and track objects (fishes) in underwater video by examining each image frame of it. For the detection process we used background subtracti...

classification of heart arrhythmia is an important step in developing devices for monitoring the health of individuals. this paper proposes a three module system for classification of electrocardiogram (ecg) beats. these modules are: denoising module, feature extraction module and a classification module. in the first module the stationary wavelet transform (swf) is used for noise reduction of ...

A top-down hierarchical system based on deep neural networks is investigated for the modeling of prosody in speech synthesis. Suprasegmental features are processed separately from segmental features and a compact distributed representation of highlevel units is learned at syllable-level. The suprasegmental representation is then integrated into a frame-level network. Objective measures show tha...

Microarray gene expression data usually consist of a large amount of genes. Among these genes, only a small fraction is informative for performing cancer diagnostic tests. This paper focuses on effective identification of informative genes. A newly developed gene selection criterion using the concept of Bayesian discriminant is used. The criterion measures the classification ability of a featur...

We show that by introducing an appropriate schema concept and exploiting the higher-level features of a resonance function in a neural network it is possible to define a form of nonmonotonic inference relation between the input and the output of the network. This inference relation satisfies some of the most fundamental postulates for nonmonotonic logics. The construction presented in the paper...

Saliency regions attract more human’s attention than other regions in an image. Low- level and high-level features are utilized in saliency region detection. Low-level features contain primitive information such as color or texture while high-level features usually consider visual systems. Recently, some salient region detection methods have been proposed based on only low-level features or hig...