Browsing by Author "Tora,H."
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Conference Object Citation Count: 3An alternative method for cell counting;(2011) Özkan, Akın; Tora, Hakan; Tora,H.; Uyar,P.; Işcan,M.; Airframe and Powerplant Maintenance; Department of Electrical & Electronics EngineeringCell counts and classification of the cells play an important role in the field of microbiology and cell biology. Although there exists many counting processes for cells of interest in suspension, the most basic cell counting process is performed by a person via the microscope. For counting cells the simplest, widely used and the most economic method is the use of hemocytometer counting. In this study, the hemocytometer counting was used but the the cells were counted by a proposed image based approach. The developed technique herein uses neural network along with the Hough transform. © 2011 IEEE.Conference Object Citation Count: 0An approach for perceptual similarity detection between audios independent of genre via metadata extraction and correlation;(2007) Tora, Hakan; Öztoprak,K.; Tora,H.; Airframe and Powerplant MaintenanceThis study presents an approach for perceptual similarity detection between audios independent of genre. The study is formed of three phases; signal pre-processing as the first phase, metadata extraction via various perceptually compatible features as the second phase, and correlation methodology for similarity identification as the third phase. The performance and relative importance of the selected features for perceptual similarity analysis are presented as testing results. Moreover, relative importance of preprocessing is introduced. Using the proposed methodology, perceptual similarity detection between genre independent audios is achieved with a 96.85% performance. Contribution highly lies on the independency of genre.Conference Object Citation Count: 0Design and Implementation of an Expressive Talking Mobile Robot: TozTorUs(Institute of Electrical and Electronics Engineers Inc., 2018) Tozan, Özalp; Tora, Hakan; Uslu,B.; Una,B.; Ceylan,E.; Computer Engineering; Airframe and Powerplant MaintenanceThis paper is about a brand new robot and all its development stages from the design to the show time. As an undergraduate research project (the LAP program at Atilim University), the robot TozTorUs is the outcome of the dense efforts of a team. With the sensors equipped, it navigates autonomously in the environment in which it is located by avoiding the obstacles. It can understand your questions and answer them using Google's speech technologies. Although it is not a humanoid robot, with eyes and mouth simulator LED displays, it is as friendly as a human. We can also control TozTorUs using a mobile phone. Apart from these, it is able to adjust its height with respect to the visitor's, thus allowing it to make an eye contact with the person. Although TozTorUs is designed for welcoming, it may also be employed for consulting, security and elderly assistance. © 2018 IEEE.Conference Object Citation Count: 0Design and Implementation of an Expressive Talking Mobile Robot: TozTorUs(Institute of Electrical and Electronics Engineers Inc., 2018) Tozan, Özalp; Tora, Hakan; Uslu,B.; Una,B.; Ceylan,E.; Computer Engineering; Airframe and Powerplant MaintenanceThis paper is about a brand new robot and all its development stages from the design to the show time. As an undergraduate research project (the LAP program at Atilim University), the robot TozTorUs is the outcome of the dense efforts of a team. With the sensors equipped, it navigates autonomously in the environment in which it is located by avoiding the obstacles. It can understand your questions and answer them using Google's speech technologies. Although it is not a humanoid robot, with eyes and mouth simulator LED displays, it is as friendly as a human. We can also control TozTorUs using a mobile phone. Apart from these, it is able to adjust its height with respect to the visitor's, thus allowing it to make an eye contact with the person. Although TozTorUs is designed for welcoming, it may also be employed for consulting, security and elderly assistance. © 2018 IEEE.Conference Object Citation Count: 1Effect of secret image transformation on the steganography process(Institute of Electrical and Electronics Engineers Inc., 2017) Tora, Hakan; Tora,H.; Gökçay, Erhan; Airframe and Powerplant Maintenance; Software EngineeringSteganography is the art of hiding information in something else. It is favorable over encryption because encryption only hides the meaning of the information; whereas steganography hides the existence of the information. The existence of a hidden image decreases Peak Signal to Noise Ratio (PSNR) and increases Mean Square Error (MSE) values of the stego image. We propose an approach to improve PSNR and MSE values in stego images. In this method a transformation is applied to the secret image, concealed within another image, before embedding into the cover image. The effect of the transformation is tested with Least Significant Bit (LSB) insertion and Discrete Cosine Transformation (DCT) techniques. MSE and PSNR are calculated for both techniques with and without transformation. Results show a better MSE and PSNR values when a transformation is applied for LSB technique but no significant difference was shown in DCT technique. © 2017 IEEE.Conference Object Citation Count: 3Emotion classification using hidden layer outputs(2012) Tora, Hakan; Tora,H.; Airframe and Powerplant MaintenanceNeural 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 Citation Count: 9Hand gesture classification using inertial based sensors via a neural network(Institute of Electrical and Electronics Engineers Inc., 2017) Akan, Erhan; Tora, Hakan; Uslu,B.; Airframe and Powerplant Maintenance; Department of Electrical & Electronics EngineeringIn this study, a mobile phone equipped with four types of sensors namely, accelerometer, gyroscope, magnetometer and orientation, is used for gesture classification. Without feature selection, the raw data from the sensor outputs are processed and fed into a Multi-Layer Perceptron classifier for recognition. The user independent, single user dependent and multiple user dependent cases are all examined. Accuracy values of 91.66% for single user dependent case, 87.48% for multiple user dependent case and 60% for the user independent case are obtained. In addition, performance of each sensor is assessed separately and the highest performance is achieved with the orientation sensor. © 2017 IEEE.Conference Object Citation Count: 1Higher order statistical analysis of Turkish phones;(IEEE Computer Society, 2014) Tora, Hakan; Uslu,B.; Airframe and Powerplant MaintenanceIn this study, histograms of Turkish phones were examined using higher order cumulants. As is known, phones constituting a language, are composed of letters as vowels and consonants. These letters can also be grouped as voiced and unvoiced phones. It is observed that unvoiced letters show a Gaussian-like distribution and result in small values of skewness and kurtosis. On the other hand, vowels and voiced consonants lead to a non-Gaussian distribution. Voiced and unvoiced phones are related with their skewness and kurtosis values. It is empirically shown that higher order cumulants are likely to be a feature in describing Turkish phones. © 2014 IEEE.Conference Object Citation Count: 1Performance evaluation of self organizing neural networks for clustering in ESM systems;(IEEE Computer Society, 2014) Gençol, Kenan; Tora, Hakan; Airframe and Powerplant Maintenance; Department of Electrical & Electronics EngineeringElectronic Support Measures (ESM) system is an important function of electronic warfare which provides the real time projection of radar activities. Such systems may encounter with very high density pulse sequences and it is the main task of an ESM system to deinterleave these mixed pulse trains with high accuracy and minimum computation time. These systems heavily depend on time of arrival analysis and need efficient clustering algorithms to assist deinterleaving process in modern evolving environments. On the other hand, self organizing neural networks stand very promising for this type of radar pulse clustering. In this study, performances of self organizing neural networks that meet such clustering criteria are evaluated in detail and the results are presented. © 2014 IEEE.Conference Object Citation Count: 2Real time infrared image enhancement;(2012) Tora, Hakan; Tora,H.; Airframe and Powerplant MaintenanceThis study evaluates the implementation of Balanced Contrast Limited Adaptive Histogram Equalization (BCLAHE) for infrared images (IR) on an embedded platform. The aim was to achieve real time performance for the operator display target application. The system configured for this aim is a dual processor media application device OMAP3530, which consists of an ARM and a DSP processor. System is configured so that hardware sources are used efficiently and various performance improvement techniques are investigated. Performance analysis is done over IR images with different dynamic range. © 2012 IEEE.Conference Object Citation Count: 0Recognition of characters on vehicle license plates;(2010) Tora, Hakan; Bora,K.; Airframe and Powerplant MaintenanceIn this study, a simple and effective method is proposed for segmenting alphanumeric and numeric characters on vehicle license plates and recognizing the segmented characters.The proposed approach is basically based on template matching technique. Features used for matching are obtained by scanning the segmented characters from left-to-right, right-to-left, top-to-bottom, and bottom-to-top. The features extracted in this way reveals the fact that how a character is moving and changing along its four-side.The character recognition is accomplished by using this information of the character.Experiments done show that successful results are obtained. ©2010 IEEE.Conference Object Citation Count: 2Recognition of Hand-Sketched digital logic gates;(Institute of Electrical and Electronics Engineers Inc., 2015) Tora, Hakan; Tora,H.; Airframe and Powerplant MaintenanceHand-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 Count: 0Segmentation of isolated words into voiced-unvoiced sound components by kurtosis;(Institute of Electrical and Electronics Engineers Inc., 2015) Tora, Hakan; Tora,H.; Airframe and Powerplant MaintenanceThis study presents a new approach to the segmentation of isolated words into their voiced/ unvoiced parts. It is well known that voiced/ unvoiced discrimination has an important role in speech synthesis and coding applications. The offered method makes this discrimination using the kurtosis values of the words. The performance of the proposed approach was tested on Turkish digit recordings from zero to nine. It has been observed that this approach segments the parts successfully in not only clean speech but also in noisy speech. © 2015 IEEE.Conference Object Citation Count: 0Tree based neural network design for emotion identification analysis;(2011) Tora, Hakan; Altinay Günler,M.; Airframe and Powerplant MaintenanceEmotion identification analysis became popular research area nowadays. It can be used in many areas such as physiology, education, murder squad, tendency to crime to get a clue about mental signals of a person. Facial expressions are kind of communication channels that carry sense signals. Therefore, they are as important as speech and body movement. Sometimes they are much more meaningful because of their naturalness. That is why it is appreciated to work on automatically recognition of facial expressions. This paper proposes an approach to recognize facial expressions by using neural network. Using one unit neural network is enough to recognize the facial expressions but using a tree structure neural network increases the accuracy of the results and the performance of the testing set. In this study, it is proposed a tree network architecture which yields better recognition performance. © 2011 IEEE.Conference Object Citation Count: 2The use of cumulants for voiced-unvoiced segments identification in speech signals;(IEEE Computer Society, 2014) Tora, Hakan; Tora,H.; Airframe and Powerplant MaintenanceIn this study, voiced-unvoiced classification performance of Turkish sounds using skewness and kurtosis is examined. The analyses show that higher order cumulants can be employed as a feature in voiced-unvoiced classification that is vital in speech processing applications. Furthermore, it has been shown that cumulants are also useful for identifying voiced and unvoiced segments in noisy speech signals. © 2014 IEEE.Article Citation Count: 0Vowel classification based on waveform shapes(ASTES Publishers, 2019) Tora, Hakan; Karacor,G.; Uslu,B.; Airframe and Powerplant MaintenanceVowel classification is an essential part of speech recognition. In classical studies, this problem is mostly handled by using spectral domain features. In this study, a novel approach is proposed for vowel classification based on the visual features of speech waveforms. In sound vocalizing, the position of certain organs of the human vocal system such as tongue, lips and jaw is very effective on the waveform shapes of the produced sound. The motivation to employ visual features instead of classical frequency domain features is its potential usage in specific applications like language education. Even though this study is confined to Turkish vowels, the developed method can be applied to other languages as well since the shapes of the vowels show similar patterns. Turkish vowels are grouped into five categories. For each vowel group, a time domain speech waveform with an interval of two pitch periods is handled as an image. A series of morphological operations is performed on this speech waveform image to obtain the geometric characteristics representing the shape of each class. The extracted visual features are then fed into three different classifiers. The classification performances of these features are compared with classical methods. It is observed that the proposed visual features achieve promising classification rates. © 2019 Advances in Science, Technology and Engineering Systems.All rights reserved.