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Yayın Biometric identification using fingertip electrocardiogram signals(Springer London Ltd, 2018-07) Güven, Gökhan; Gürkan, Hakan; Güz, ÜmitIn this research work, we present a newly fingertip electrocardiogram (ECG) data acquisition device capable of recording the lead-1 ECG signal through the right- and left-hand thumb fingers. The proposed device is high-sensitive, dry-contact, portable, user-friendly, inexpensive, and does not require using conventional components which are cumbersome and irritating such as wet adhesive Ag/AgCl electrodes. One of the other advantages of this device is to make it possible to record and use the lead-1 ECG signal easily in any condition and anywhere incorporating with any platform to use for advanced applications such as biometric recognition and clinical diagnostics. Furthermore, we proposed a biometric identification method based on combining autocorrelation and discrete cosine transform-based features, cepstral features, and QRS beat information. The proposed method was evaluated on three fingertip ECG signal databases recorded by utilizing the proposed device. The experimental results demonstrate that the proposed biometric identification method achieves person recognition rate values of 100% (30 out of 30), 100% (45 out of 45), and 98.33% (59 out of 60) for 30, 45, and 60 subjects, respectively.Yayın MIMO sinyalleri için uzay-zaman blok kodu klasifikasyonu(IEEE, 2014-04-26) Turan, Merve; Öner, Mustafa Mengüç; Çırpan, Hakan AliBilinmeyen haberleşme sinyallerinin gözü kapalı ve işbirliksiz tanınması için geliştirilen teknikler, hem askeri hem de sivil uygulamalarda kullanım bulmuştur. Çok Girdili Çok Çıktılı (MIMO) haberleşme sistemleri, sinyal tanıma sistemleri için üstesinden gelinmesi gereken yeni problemler ortaya koymaktadır. MIMO haberleşmesinde kullanılan uzay zaman kodlarının gözükapalı tanınması bu problemlerin en önemlilerinden biri olarak görülebilir. Bu çalışmada uzay zaman blok kodlanmış sinyal vektörlerinin döngüsel-durağan (cyclostationary) karakteristiklerinin farklı uzay zaman blok kodlarını birbirinden ayırdetmek amacıyla kullanıldığı yenilikçi uzay-zaman kodu tanıma algoritmaları öneriyoruz.Yayın VİSKON-RS : Uzaktan algılama ile hızlı afet hasar analiz yazılımı(IEEE, 2015-06-19) Kahraman, Fatih; İmamoğlu, Mümin; Özcan, Büşra Yüksel; Huruoğlu, Cengiz; Alasağ, Tolga; Gemici, Ömer Faruk; Hocaoğlu, Muhammet A.; Ateş, Hasan FehmiAfet sonrası, acil müdahale ekiplerinin yönlendirilmesi ve iyileştirme çalışmalarının planlanması amacıyla hızlı hasar değerlendirmesine ihtiyaç duyulmaktadır. Bu çalışmada, AFAD ihtiyaçları doğrultusunda uzaktan (uzay/hava) algılama teknolojileri ile elde edilen görüntülerin afet hasar analizinde kullanılmasına yönelik VİSKON-RS yazılımı geliştirilmiştir. Geliştirilen yazılım; deprem, sel ve orman yangını gibi afet türlerinin hasar analizlerine özelleşmiş uygulamalar içermektedir. Ayrıca genel görüntü analizinde kullanılabilecek değişiklik analizi, eğitimli/eğitimsiz sınıflandırma, nesne tabanlı görüntü analizi ve doku analizi gibi uygulamalar yazılıma entegre edilmiştir. VİSKON-RS yazılımın temel amacı, afet sonrası uzaktan algılama verilerinin, açılması, işlenmesi, analiz edilmesi, sonuçların sergilenmesi ve karar destek sistemlerine aktarılması adımlarını içeren bütünleşik bir yazılım çözümü sunmaktır.Yayın CNN-Based deep learning architecture for electromagnetic imaging of rough surface profiles(IEEE, 2022-10) Aydın, İzde; Budak, Güven; Sefer, Ahmet; Yapar, AliA convolutional neural network (CNN) based deep learning (DL) technique for electromagnetic imaging of rough surfaces separating two dielectric media is presented. The direct scattering problem is formulated through the conventional integral equations and the synthetic scattered field data is produced by a fast numerical solution technique which is based on Method of Moments (MoM). Two different special CNN architectures are designed and implemented for the solution of the inverse rough surface imaging problem wherein both random and deterministic rough surface profiles can be imaged. It is shown by a comprehensive numerical analysis that the proposed deep-learning (DL) inversion scheme is very effective and robust.Yayın Feature extraction in shape recognition using segmentation of the boundary curve(Elsevier Science BV, 1997-10) Özuğur, Timuçin; Denizhan, Yağmur; Panayırcı, ErdalWe present a new method for feature extraction of two-dimensional shape information based on segmentation of the boundary curve. This approach partitions closed shapes into segments and finds their angular spans. The number of segments and the angular spans form the first two feature parameters of a given shape. Fourier coefficients of all segments constitute the final feature parameters. The algorithm renders the shapes independent of scale, rotation and translation, The main advantage of this method is to speed up substantially the recognition process of the shapes, mainly because it is possible to design the classification rule in a hierarchical way. It is therefore suitable for objects to be sorted in a factory environment where the silhouette boundary supplies sufficient information for identification.Yayın Hierarchical quantization indexing for wavelet and wavelet packet image coding(Elsevier Science BV, 2010-02) Ateş, Hasan Fehmi; Tamer, EnginIn this paper, we introduce the quantization index hierarchy, which is used for efficient coding of quantized wavelet and wavelet packet coefficients. A hierarchical classification map is defined in each wavelet subband, which describes the quantized data through a series of index classes. Going from bottom to the top of the tree, neighboring coefficients are combined to form classes that represent some statistics of the quantization indices of these coefficients. Higher levels of the tree are constructed iteratively by repeating this class assignment to partition the coefficients into larger Subsets. The class assignments are optimized using a rate-distortion cost analysis. The optimized tree is coded hierarchically from top to bottom by coding the class membership information at each level of the tree. Context-adaptive arithmetic coding is used to improve coding efficiency. The developed algorithm produces PSNR results that are better than the state-of-art wavelet-based and wavelet packet-based coders in literature.
