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Conference Object Citation - WoS: 1Recognition of Hand-Sketched Digital Logic Gates(Ieee, 2015) Gul, Nuray; Tora, HakanHand-Sketched circuit recognition is a very useful tool in engineering area. Because most of the engineers prefer to design their circuits on the paper firstly. So, this can cause time wasting and some mistakes. In this study, which is based on the solving these kinds of problems, classification and recognition of the handwritten digital logic gates according to their complex and scalar FDs (Fourier Descriptors) is presented. Test results are obtained as 84.3 % accuracy rate for complex FDs, 98.6 % for scalar FDs. Then these results are compared and decided the optimum FDs type for this study.Conference Object Citation - Scopus: 2Recognition of Hand-Sketched Digital Logic Gates;(Institute of Electrical and Electronics Engineers Inc., 2015) Gül,N.; Tora,H.Hand-Sketched circuit recognition is a very useful tool in engineering area. Because most of the engineers prefer to design their circuits on the paper firstly. So, this can cause time wasting and some mistakes. In this study, which is based on the solving these kinds of problems, classification and recognition of the handwritten digital logic gates according to their complex and scalar FDs (Fourier Descriptors) is presented. Test results are obtained as 84.3 % accuracy rate for complex FDs, 98.6 % for scalar FDs. Then these results are compared and decided the optimum FDs type for this study. © 2015 IEEE.Conference Object Citation - WoS: 1Lip Shape Based Emotion Identification(Ieee, 2016) Gul, Nuray; Tora, HakanEmotion recognition systems have an important role to play in the human-computer interactive applications (HCI). These systems are using facial features of face images and they are verifying or identifying the emotions. In this study, emotion identification algorithms are improved by using just mouth region features of a face. Region of interest (mouth region) is detected by Viola-Jones algorithms from video frames which are including different emotional face expressions. Outer boundaries of lip shapes are extracted by manually and calculated the scalar Fourier Descriptors (FDs) of the boundaries. Classification and recognition of the emotions is presented according to scalar FDs of lip contours. Test results are obtained as 93.9 % accuracy rate for scalar FDs.Article Citation - WoS: 4An Eye-Controlled Wearable Communication and Control System for Als Patients: Smarteyes(Yildiz Technical Univ, 2017) Sumer, Emre; Uslu, I. Baran; Turker, MustafaALS (Amyotrophic Lateral Sclerosis) is a progressive neurodegenerative disease that involves the malfunctioning of motor neurons. The ability of the brain to initiate and control muscle movement is lost subsequent to death of motor neurons. People with ALS present the greatest challenge regarding communication issues. Besides, caring for a loved one with ALS is not an easy task. In this study, we developed an eye-controlled wearable system called "SmartEyes" which improves the life qualities of ALS patients and their caregivers by offering two important skills. The first skill is communicating through predefined voice messages generated by a computer and the second one is controlling several peripherals located in the patient's environment. The developed system is novel in that; the patients can easily vocalize their needs and requests with a few sequential eye movements. Moreover, they can control several household items including desk lamp, rolling curtain, television and air conditioner in the same way. The preliminary experiments showed that the performance of the system is satisfactory. The accuracy of the system commands based on pupil gaze direction was tested on several users and about an accuracy of 89% was achieved. It is believed that the developed system has attracted the patients' and their caregivers' interest very much and this is the main motivation in improving our system.Conference Object Citation - Scopus: 3Emotion classification using hidden layer outputs(2012) Günler,M.A.; Tora,H.Neural network (NN) with Multi-Layer Perceptron (MLP) is a supervised learning algorithm composed of artificial neurons. Multilayer NN is capable of solving nonlinear classification problems such as emotion identification by using facial expressions that is presented in this paper. Hidden layer outputs of NN provide useful information about facial appearance. This study addresses that without fully training NN hidden layer outputs can be used as feature. It is shown that an acceptable recognition rate is obtained by means of hidden layer outputs. © 2012 IEEE.Conference Object Part-Based Object Extraction for Complex Objects(Ieee, 2014) Koyuncu, Murat; Cetinkaya, BasarIndexing requirement for efficient accessing to visual data has been increased with the widespread use of multimedia applications. Satisfaction of this requirement mostly depends on the automatic extraction of objects in the visual data. In this study, component-based object extraction method is compared with object extraction in its entirety. Applied method, implemented system and conducted tests are presented in this paper. Test results show that, even in the case of a good segmentation is achieved for whole object, object components are classified more successfully compared to whole object.Conference Object Part-Based Object Extraction for Complex Objects;(IEEE Computer Society, 2014) Koyuncu,M.; Cetinkaya,B.Indexing requirement for efficient accessing to visual data has been increased with the widespread use of multimedia applications. Satisfaction of this requirement mostly depends on the automatic extraction of objects in the visual data. In this study, component-based object extraction method is compared with object extraction in its entirety. Applied method, implemented system and conducted tests are presented in this paper. Test results show that, even in the case of a good segmentation is achieved for whole object, object components are classified more successfully compared to whole object. © 2014 IEEE.Conference Object A Component-Based Object Detection Method Extended With a Fuzzy Inference Engine(Institute of Electrical and Electronics Engineers Inc., 2015) Koyuncu,M.; Cetinkaya,B.In this paper, we propose a component-based object detection method extended with the fuzzy inference technique. The proposed method detects constituent components of a complex object instead of a whole object in images. For component detection, multiple multi-class support vector machines (SVM) are used in parallel. Each SVM classifies the candidate component using a different low-level image feature. The obtained results are fused to reach a decision about the component. Then, a fuzzy object extractor determines the whole object considering the detected components and their geometric configurations. The fuzzy object extractor is a fuzzy inference engine which tests various combinations of detected components and their fuzzified directions and distances. The initial tests yield promising results and encourage further studies to extend proposed method. © 2015 IEEE.Conference Object A Component-Based Object Detection Method Extended With a Fuzzy Inference Engine(Ieee, 2015) Koyuncu, Murat; Cetinkaya, BasarIn this paper, we propose a component-based object detection method extended with the fuzzy inference technique. The proposed method detects constituent components of a complex object instead of a whole object in images. For component detection, multiple multi-class support vector machines (SVM) are used in parallel. Each SVM classifies the candidate component using a different low-level image feature. The obtained results are fused to reach a decision about the component. Then, a fuzzy object extractor determines the whole object considering the detected components and their geometric configurations. The fuzzy object extractor is a fuzzy inference engine which tests various combinations of detected components and their fuzzified directions and distances. The initial tests yield promising results and encourage further studies to extend proposed method.
