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Conference Object Citation - Scopus: 3Gender Prediction by Using Local Binary Pattern and K Nearest Neighbor and Discriminant Analysis Classifications;(Institute of Electrical and Electronics Engineers Inc., 2016) Camalan,S.; Sengul,G.In this study, gender prediction is investigated for the face images. To extract the features of the images, Local Binary Pattern (LBP) is used with its different parameters. To classify the images male or female, K-Nearest Neighbors (KNN) and Discriminant Analysis (DA) methods are used. Their performances according to the LBP parameters are compared. Also classification methods' parameters are changed and the comparison results are shown. These methods are applied on FERET database with 530 female and 731 male images. To have better performance, the face parts of the images are cropped then feature extraction and classification methods applied on the face part of the images. © 2016 IEEE.Conference Object Deep Learning and Current Trends in Machine Learning(Institute of Electrical and Electronics Engineers Inc., 2018) Bostan,A.; Ekin,C.; Sengul,G.; Karakaya,M.; Tirkes,G.Academic interest and commercial attention can be used to identify how much potential a novel technology may have. Since the prospective advantages in it may help solving some problems that are not solved yet or improving the performance of readily available ones. In this study, we have investigated the Web of Science (WOS) indexing service database for the publications on Deep Learning (DL), Machine Learning (ML), Convolutional Neural Networks (CNN), and Image Processing to reveal out the current trend. The figures indicate the strong potential in DL approach especially in image processing domain. © 2018 IEEE.Article Citation - Scopus: 2Trends in E-Governments: From E-Govt To M-Govt(2013) Ertürk,K.L.; Sengul,G.; Rehan,M.New technological advancement and availability in mobile devices, technology, applications and networks have made it possible for a common citizens to access information and transact services while on the move. This gives an opportunity for governments to provide such services to citizens at the minimum cost. E-government practice and routine in public sectors are being supplemented and moving towards to m-governement (mobile government). M-Government can be defined as the massive usage of mobile devices with their applications to develope a quick connection and response between citizen and public sector authorities. M-government is a support of improving the quality, time saving and usability of e-government applications around the clock from any location. The existing technological foundations, applications and services support the idea that m-government will be a significant part of e-government efforts. The policy makers and IT professionals need get ready to embrace these developments and participate in the ways to enhance e-government activities through m-government. This transformational process is going on around the world. This article will investigate where governmental organizations are becomming mobil government organization to quickely reach to their citizens and increasing communication with them beyound the limits. © IDOSI Publications, 2013.Conference Object A Comparison of Pattern Recognition Approaches for Recognizing Handwriting in Arabic Letters(Institute of Electrical and Electronics Engineers Inc., 2021) Douma,A.; Ahmed,A.A.; Sengul,G.; Santhosh,J.; Jomah,O.S.M.; Ibrahim Salem,F.G.For Arabic letters recognition, we achieve three of pattern recognition approaches namely gray level co-occurrence matrix (GLCM), local binary pattern recognition (LBP) and artificial neural network (ANN) and compare between them to result best performance. Two of these methods level co-occurrence matrix and local binary pattern recognition are used for feature extraction whereas in artificial neural network (ANN) we use the intensity values of pixels for input of the neural network. Two classifiers are used, the K-Nearest Neighbor classifier (KNN) for the LBP, GLCM and neural network classifier for (ANN) artificial neural network. Also, we evaluate the results by using leave one person out approach, fold classification and leave one out. © 2021 IEEE.Conference Object Citation - Scopus: 1Applying the Histogram of Oriented Gradients To Recognize Arabic Letters(Institute of Electrical and Electronics Engineers Inc., 2021) Douma,A.; Sengul,G.; Ibrahim Salem,F.G.; Ali Ahmed,A.the aim of this paper is to recognize the Arabic handwriting letters by using histogram of oriented gradients (HOG). We collected 2240 letters by 8 people, each person wrote 28 alphabet letter 10 times. First of all we resize All 2240 hand writing letter of Arabic Alphabet as images(pre-processing) after that extract these images by using one of feature extraction methods which is histogram of oriented gradients (HOG).For classification, the K-Nearest Neighbor (KNN) is used. The results are shown by using 1120 images in the one case and 2240 images in the second case and evaluate these results with the confusion matrix. Other cases we used leave one out (LOO), 2-fold classification and leave one out cross validation. The best fully performance of HOG was with leave one out technique because of the ability of HOG algorithm to capture the shape of letter in the image according to its edges (gradients). © 2021 IEEE.Conference Object Deep Learning and Current Trends in Machine Learning(Institute of Electrical and Electronics Engineers Inc., 2018) Bostan,A.; Ekin,C.; Sengul,G.; Karakaya,M.; Tirkes,G.Academic interest and commercial attention can be used to identify how much potential a novel technology may have. Since the prospective advantages in it may help solving some problems that are not solved yet or improving the performance of readily available ones. In this study, we have investigated the Web of Science (WOS) indexing service database for the publications on Deep Learning (DL), Machine Learning (ML), Convolutional Neural Networks (CNN), and Image Processing to reveal out the current trend. The figures indicate the strong potential in DL approach especially in image processing domain. © 2018 IEEE.Conference Object Citation - Scopus: 1Method Proposal for Distinction of Microscope Objectives on Hemocytometer Images;(Institute of Electrical and Electronics Engineers Inc., 2016) Ozkan,A.; Isgor,S.B.; Sengul,G.Hemocytometer is a special glass plate apparatus used for cell counting that has straight lines (counting chamber) in certain size. Leveraging this special lam and microscope, a cell concentration on an available cell suspension can be estimated. The automation process of hemocytometer images will assist several research disciplines to improve consistency of results and to reduce human labor. Different objective measurements can be utilized to analyze a cell sample on microscope. These differences affect the detail of image content. Basically, while the objective value is getting increased, image scale and detail level taken from image will increase, yet visible area becomes narrower. Due to this variation, different self-cell counting approaches should be developed for images taken with different objective values. In this paper, using the hemocytometer images gathered from a microscope, a novel approach is introduced for which can estimate objective values of a microscope with machine learning methods automatically. For this purpose, a frequency-based visual feature is proposed which embraces hemocytometer structure well. As a result of the conducted tests, %100 distinction accuracy is achieved with the proposed method. © 2016 IEEE.
