In this study a new dataset are prepared for neuromuscular diseases using scanning EMG method and four new features are extracted. These features are maximum amplitude, phase duration at the maximum amplitude, maximum ...

Order to save energy and to use energy resources efficiently, automatic occupancy determination based on sensor information is performed and energy is adjusted according to the demand in a closed area. In this study is ...

Fingerprint detection is one of the primary methods for identifying individuals. Gray Level Co-occurrence Matrix (GLCM) is the oldest and prominent statistical textual feature extraction method applied in many fields for ...

In this study, it was aimed to classify the electrical signals recorded from human brain during different season (summer-winter) videos as stimuli. Data have been recorded using 14 channels EEG from four male participants. ...

Processing of brain images has some difficulties because of the large data size and complexity of the data. Deep learning facilitates hierarchicical feature extraction automatically. However the optimization of deep nets ...

Development of intelligent care system for elder people have been investigated in recent years. In this study, to detect emergency situations for elder people, activity classification was aimed using on body sensor data. ...

This paper proposes a novel high-performance gradient-based local descriptor that handles the prominent challenges of face recognition such as resistance against rotational, illuminative changes as well as noise effects. ...

Timely and accurate diagnosis of intraabdominal organ injuries due to trauma is critical. Computer Assisted Detection (CAD) systems are rapidly developing techniques to segment the organs or to detect the pathologies in ...