Özcan, Zubeyir; Kayikçioglu, Ilknur; Yildirim, Omer; Köse, Cemal; Kayikçioglu, Temel

In this study, A user-friendly, versatile and easily accessible educational software design was done by using NEURON hoc programming in order to investigate the dynamics, biophysical properties of nerve cells and their responses to various stimulation. With the help of interfaces which prepared for users to be assisted visually, it is aimed to be able to easily perform almost any application desired. This software allows users to perform their simulations without the need to write any code. Considering the features given in detail in the study, it has been suggested to use the software in neuroscience education.

Dogan, Ramazan Ozgur; Dogan, Hulya; Köse, Cemal

Virtual mouse implemented with hand gesture tracking based on image is one of studies in human-computer interaction. In this study that human-computer interaction is implemented with virtual mouse is purposed. This study consists of three main steps that are hand gesture tracking, features of hand region extraction and classification of these features. In this study hand gesture tracking is generated with Camshift (Continuously Adaptive Mean Shift) algorithm, features of hand gestures are extracted with bag of visual words and these features are classified with support vector machines. Detailed tests are performed to compare success of tracking, features extraction and classisfication methods and that this system works successfully is shown.

Dogan, Ramazan Ozgur; Köse, Cemal

The devices such as mouse, keyboard used for controlling of computer have various limitations. The users must make physical contact with the devices and have a restricted away because of connection with wire to control computer by using these devices. Traditional communication devices for computer-person can't provide user wireless computer control without any physical. Inthis study, Computer monitoring and controlling with hand movements are implemented by using image proccesing and computer vision techniques to minimize these limitations. In proposed study, firstly it is expected that the user enters camera's field of view using computer camera. face of user entering the camera's field of view is detected with Haar Classifier. Hand region is detected by finding the dynamic range of skin color in YCbCr color space from the facial region. The hand region is tracked with Biggest Blob Tracking Technique, and features of hand are extracted by using Convexity Defect-Hull during tracking. Finally, position of mouse is controlled according to features of hand region, and Computer monitoring and controlling with hand movements are implemented bu tracking hand gestures.