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Full-Text Articles in Physical Sciences and Mathematics
Classification Of Eeg Signals Of Familiar And Unfamiliar Face Stimuli Exploiting Most Discriminative Channels, Abdurrahman Özbeyaz, Sami̇ Arica
Classification Of Eeg Signals Of Familiar And Unfamiliar Face Stimuli Exploiting Most Discriminative Channels, Abdurrahman Özbeyaz, Sami̇ Arica
Turkish Journal of Electrical Engineering and Computer Sciences
The objective of the study is to classify electroencephalogram signals recorded in a familiar and unfamiliar face recognition experiment. Frontal views of familiar and unfamiliar face images were shown to 10 volunteers in different sessions. In contrast to previous studies, no marker button was used during the experiment. Participants had to decide whether the displayed face was familiar or unfamiliar at the instant of stimulus presentation. The signals were analyzed in the preprocessing, channel selection, feature extraction, and classification stages. The novel two-feature extraction and eight-channel selection methods were applied to the analyses. Sixteen classification results were compared and the …
A Comparison Of Feature Extraction Techniques For Malware Analysis, Mohammad Imran, Muhammad Tanvir Afzal, Muhammad Abdul Qadir
A Comparison Of Feature Extraction Techniques For Malware Analysis, Mohammad Imran, Muhammad Tanvir Afzal, Muhammad Abdul Qadir
Turkish Journal of Electrical Engineering and Computer Sciences
The manifold growth of malware in recent years has resulted in extensive research being conducted in the domain of malware analysis and detection, and theories from a wide variety of scientific knowledge domains have been applied to solve this problem. The algorithms from the machine learning paradigm have been particularly explored, and many feature extraction methods have been proposed in the literature for representing malware as feature vectors to be used in machine learning algorithms. In this paper we present a comparison of several feature extraction techniques by first applying them on system call logs of real malware, and then …
Late Fusion Of Facial Dynamics For Automatic Expression Recognition, Alessandra Bandrabur, Laura Florea, Cornel Florea, Matei Mancas
Late Fusion Of Facial Dynamics For Automatic Expression Recognition, Alessandra Bandrabur, Laura Florea, Cornel Florea, Matei Mancas
Turkish Journal of Electrical Engineering and Computer Sciences
Installment of a facial expression is associated with contractions and extensions of specific facial muscles. Noting that expression is about changes, we present a model for expression classification based on facial landmarks dynamics. Our model isolates the trajectory of facial fiducial points by wrapping them up in relevant features and discriminating among various alternatives with a machine learning classification system. The used features are geometric and temporal-based and the classification system is represented by a late fusion framework that combines several neural networks with binary responses. The proposed method is robust, being able to handle complex expression classes.
Multiclass Semantic Segmentation Of Faces Using Crfs, Khalil Khan, Nasir Ahmad, Khalil Ullah, Irfanud Din
Multiclass Semantic Segmentation Of Faces Using Crfs, Khalil Khan, Nasir Ahmad, Khalil Ullah, Irfanud Din
Turkish Journal of Electrical Engineering and Computer Sciences
Multiclass semantic image segmentation is widely used in a variety of computer vision tasks, such as object segmentation and complex scene understanding. As it decomposes an image into semantically relevant regions, it can be applied in segmentation of face images. In this paper, an algorithm based on multiclass semantic segmentation of faces is proposed using conditional random fields. In the proposed model, each node corresponds to a superpixel, while the neighboring superpixels are connected to nodes through edges. Unlike previous approaches, which rely on three or four classes, the label set is extended here to six classes, i.e. hair, eyes, …