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Publication Metadata only 3D object matching via multivariate shape distributions(Institute of Electrical and Electronics Engineers (IEEE), 2005) Akgül, C.B.; Sankur, B.; Schmitt, F.; Department of Computer Engineering; Yemez, Yücel; Faculty Member; Department of Computer Engineering; College of Engineering; 1079073B nesne eşleştirme literatüründe, problemi şekil dağılımlarının karşılaştırılmasına indirgeyen yöntemler bulunmaktadır. Şekil dağılımı, 3B nesne yüzeyi üzerinde hesaplanan bir işlevin değerlerinin olasılık dağılımı olarak tanımlanır. Bu çalışmada varolan yöntemi, birden çok işlevin getirdiği şekil bilgisinden aynı anda yararlanacak şekilde genişletiyoruz. Çokboyutlu şekil dağılımları adını verdiğimiz bu 3B nesne betimleyicilerini, örnek bir 3B nesne veri tabanındaki nesneler için parametrik olmayan yaklaşımlarla kestiriyor, karşılaştırmaları alternatif metrikler yoluyla yapıyoruz. Elde edilen kesinlik-geri getirme eğrileri çokboyutlu şekil dağılımlarının karşılaştırılmasının yeni bir 3B nesne eşleştirme paradigması olabileceğini göstermektedir.Publication Metadata only A combined interval and floating-point reciprocal unit(IEEE, 2005) N/A; N/A; Department of Computer Engineering; Küçükkabak, Umut; Akkaş, Ahmet; Master Student; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/AInterval arithmetic is one technique for accurate and reliable computing. Among interval arithmetic operations, division is the most time consuming operation. This paper presents the design and implementation of a combined interval and floating-point reciprocal unit. To compute the reciprocal of an operand, an initial approximation is computed first and then iterated twice by Newton-Raphson iteration. The combined interval and floating-point reciprocal unit computes the reciprocal of a double precision floating-point number in eleven clock cycles and the reciprocal of an interval in twenty-one clock cycles. The unit is implemented in VHDL and synthesized to estimate the area and the worst case delay. Simulation results showed that the least significant bit of the floating-point result cannot be guaranteed to be same for all cases compared to the result based on an infinite precision. For interval reciprocal, however, the true result is contained in the result interval.Publication Metadata only A comparison of data representation types, feature types and fusion techniques for 3D face biometry(European Association for Signal Processing, 2006) Dutaǧaci, H.; Sankur, B.; Department of Computer Engineering; Yemez, Yücel; Faculty Member; Department of Computer Engineering; College of Engineering; 107907This paper focuses on the problems of person identification and authentication using registered 3D face data. The face surface geometry is represented alternately as a point cloud, a depth image or as voxel data. Various local or global feature sets are extracted, such as DFT/DCT coefficients, ICA- and NMF- projections, which results in a rich repertoire of representations/features. The identification and authentication performance of the individual schemes are compared. Fusion schemes are invoked, to improve the performance especially in the case when there are only few samples per subject.Publication Metadata only A containerized proof-of-concept implementation of LightChain system(Ieee, 2020) N/A; N/A; Department of Computer Engineering; N/A; Department of Computer Engineering; Department of Computer Engineering; Hassanzadeh-Nazarabadi, Yahya; Nayal, Nazir; Hamdan, Shadi Sameh; Özkasap, Öznur; Küpçü, Alptekin; PhD Student; Faculty Member; Master Student; Faculty Member; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; N/A; N/A; 113507; 168060LightChain is the first Distributed Hash Table (DHT)-based blockchain with a logarithmic asymptotic message and memory complexity. In this demo paper, we present the software architecture of our open-source implementation of LightChain, as well as a novel deployment scenario of the entire LightChain system on a single machine aiming at results reproducibility.Publication Metadata only A deep learning approach for data driven vocal tract area function estimation(IEEE, 2018) N/A; Department of Computer Engineering; Asadiabadi, Sasan; Erzin, Engin; PhD Student; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 34503In this paper we present a data driven vocal tract area function (VTAF) estimation using Deep Neural Networks (DNN). We approach the VTAF estimation problem based on sequence to sequence learning neural networks, where regression over a sliding window is used to learn arbitrary non-linear one-to-many mapping from the input feature sequence to the target articulatory sequence. We propose two schemes for efficient estimation of the VTAF; (1) a direct estimation of the area function values and (2) an indirect estimation via predicting the vocal tract boundaries. We consider acoustic speech and phone sequence as two possible input modalities for the DNN estimators. Experimental evaluations are performed over a large data comprising acoustic and phonetic features with parallel articulatory information from the USC-TIMIT database. Our results show that the proposed direct and indirect schemes perform the VTAF estimation with mean absolute error (MAE) rates lower than 1.65 mm, where the direct estimation scheme is observed to perform better than the indirect scheme.Publication Open Access A diversity combination model incorporating an inward bias for interaural time-level difference cue integration in sound lateralization(Multidisciplinary Digital Publishing Institute (MDPI), 2020) N/A; Department of Computer Engineering; Mojtahedi, Sina; Erzin, Engin; Ungan, Pekcan; Faculty Member; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; School of Medicine; N/A; 34503; N/AA sound source with non-zero azimuth leads to interaural time level differences (ITD and ILD). Studies on hearing system imply that these cues are encoded in different parts of the brain, but combined to produce a single lateralization percept as evidenced by experiments indicating trading between them. According to the duplex theory of sound lateralization, ITD and ILD play a more significant role in low-frequency and high-frequency stimulations, respectively. In this study, ITD and ILD, which were extracted from a generic head-related transfer functions, were imposed on a complex sound consisting of two low- and seven high-frequency tones. Two-alternative forced-choice behavioral tests were employed to assess the accuracy in identifying a change in lateralization. Based on a diversity combination model and using the error rate data obtained from the tests, the weights of the ITD and ILD cues in their integration were determined by incorporating a bias observed for inward shifts. The weights of the two cues were found to change with the azimuth of the sound source. While the ILD appears to be the optimal cue for the azimuths near the midline, the ITD and ILD weights turn to be balanced for the azimuths far from the midline.Publication Metadata only A diversity combination model incorporating an inward bias for interaural time-level difference cue integration in sound lateralization(MDPI, 2020) N/A; N/A; Department of Computer Engineering; N/A; Mojtahedi, Sina; Erzin, Engin; Ungan, Pekcan; PhD Student; Faculty Member; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; School of Medicine; N/A; 34503; N/AA sound source with non-zero azimuth leads to interaural time level differences (ITD and ILD). Studies on hearing system imply that these cues are encoded in different parts of the brain, but combined to produce a single lateralization percept as evidenced by experiments indicating trading between them. According to the duplex theory of sound lateralization, ITD and ILD play a more significant role in low-frequency and high-frequency stimulations, respectively. In this study, ITD and ILD, which were extracted from a generic head-related transfer functions, were imposed on a complex sound consisting of two low- and seven high-frequency tones. Two-alternative forced-choice behavioral tests were employed to assess the accuracy in identifying a change in lateralization. Based on a diversity combination model and using the error rate data obtained from the tests, the weights of the ITD and ILD cues in their integration were determined by incorporating a bias observed for inward shifts. The weights of the two cues were found to change with the azimuth of the sound source. While the ILD appears to be the optimal cue for the azimuths near the midline, the ITD and ILD weights turn to be balanced for the azimuths far from the midline.Publication Metadata only A framework for histogram-induced 3D descriptors(European Association for Signal Processing, 2006) Akgül, C.B.; Sankur, B.; Schmitt, F.; Department of Computer Engineering; Yemez, Yücel; Faculty Member; Department of Computer Engineering; College of Engineering; 107907We present a novel framework to describe 3D shapes, based on modeling the probability density of their shape functions. These functions are conceived to reflect the 3D geometrical properties of the shape surfaces. The densities are modeled as mixtures of Gaussians, each component being the distribution induced by a mesh triangle. A fast algorithm is developed exploiting both the special geometry of 3D triangles with numerical approximations as well as a transform technique. We test and compare the proposed descriptors to other histogram-based methods on two different 3D model databases. It is shown that 3D shape descriptors outperform all of its competitors except one in retrieval applications. Furthermore our methodology provides a fertile ground to introduce and test new descriptors.Publication Metadata only A new interface for affective state estimation and annotation from speech(Institute of Electrical and Electronics Engineers (IEEE), 2019) Fidan, Umut; Tomar, Deniz; Ozdil, P. Gizem; Department of Computer Engineering; Erzin, Engin; Faculty Member; Department of Computer Engineering; College of Engineering; 34503Emotion recognition from speech has been an important research area in the recent past. In this study, the purpose is to predict the emotion annotations better for robot/agent and hence to develop a more human-like interaction between human and robot/agent. In this context, the emotion annotations of human-human interactions, acoustic feature extraction and spectrogram images are carried on human-human dyadic conversations. In the first study, the statistical summary results are matched with the corresponding annotation and emotion recognition is achieved by using Support Vector Machines. In the second study, a sliding window of a certain size and overlapping intervals are matched with the corresponding annotation and the machine is trained by using Convolutional Neural Networks. Consequently, a user interface is designed to contain the works aforementioned. Also, the models obtained are tested with the databases JESTKOD and CreativeIT on this interface, and yield promising results for human-like robot/agents./ Öz:Konuşmadan duygu tanıma, yakın geçmişte önemli bir araştırma alanı olmuştur. Bu çalışmada hedef, robot/aracının duygu durum değerlerini daha iyi tahmin etmesi ve dolasıyla in- san ve robot/aracı arasında daha insansı bir etkileşim geliştirmektir. Bu bağlamda, insan-insan etkileşiminde etiketlenmiş duygu durum değerleri, istatistiksel akustik ve spektral imge öznite- ˘ likleri insan-insan ikili ileti¸simine uygulanmı¸stır. ˙Ilk çalı¸smada, istatistiksel akustik öznitelikler ile etiketlemeler eşleştirilmiş ve Destek Vektör Makineleri kullanılarak duygu durum kestirimi yapılmıştır. ikinci kısımda, belli pencere aralıklarına sahip, örtüşen ve kayan spektral imgeler duygu durum değerleriyle eşleştirilmiş ve üzerinde Evrişimsel Sinir Ağları kullanılarak duygu durum kestirimi yapılmıştır. Son olarak, bu iki kestirim yöntemini barındıran yeni bir kullanıcı arayüzü tasarlanmıştır. Ayrıca, elde edilen modeller bu arayüz üzerinde JESTKOD ve CreativeIT veritabanları ile test edilmiş ve insan benzeri robot/aracılar için umut verici sonuçlar vermiştir.Publication Metadata only A novel utility based metric and routing for energy efficiency in software defined networking(Institute of Electrical and Electronics Engineers (IEEE), 2019) N/A; Department of Computer Engineering; Assefa, Beakal Gizachew; Özkasap, Öznur; PhD Student; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 113507Software defined networking (SDN) is a rapidly growing networking paradigm in both industry and research areas, with network programmability as its powerful feature which enables propagating changes in the network easily. However, the links and switches are designed to accommodate maximum traffic load and their power consumption is not traffic aware. The logically centralized control in SDN enables dynamically minimizing the energy consumption of the links and the switches by diverting paths of packets. Energy efficiency and performance are opposite objectives that have to be addressed simultaneously. As the main contributions in this study, we first propose an energy efficiency metric Energy Profit Threshold (EPT) that is applicable to SDN. Then, we provide Integer Programming (IP) formulation with the objective of maximizing the EPT of a software defined network environment. Experimental results show that maximizing the EPT value exhibits energy saving of more than 35 % as compared to other utility based energy saving algorithms.