Bilgisayar Mühendisliği Bölümü Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1940
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Conference Object Citation - WoS: 1Citation - Scopus: 1Face Recognition With Local Zernike Moments Features Around Landmarks(IEEE, 2016) Gökmen, Muhittin; Gökmen, Muhittin; 02.02. Department of Computer Engineering; 02. Faculty of Engineering; 01. MEF UniversityIn this paper, a new method that extracts the features from the complex Local Zernike Moments (LZM) images around facial landmarks is proposed. In this method, multiple grids which are in different sizes are located on landmarks and Phase-Magnitude (PM) histograms are calculated in each cells of these grids. The PM histograms are calculated for every component of LZM and the feature vectors are created by concatenating these histograms. By reducing the dimensionality of these vectors using Whitened Principle Component Analysis, more robust descriptors are constructed. It is shown that the state-of-the-art results are obtained in the experiments performed on FERET database using the proposed method. © 2016 IEEE.Conference Object Citation - Scopus: 7The Use of Neurometric and Biometric Research Methods in Understanding the User Experience During Product Search of First-Time Buyers in E-Commerce - Conference Paper(Springer, 2017) Rızvanoğlu, Kerem; Çakar, Tuna; Çakar, Tuna; Öztürk, Özgürol; Zengin Çelik, Deniz; Çelik, Deniz Zengin; 02.02. Department of Computer Engineering; 02. Faculty of Engineering; 01. MEF UniversityUnderstanding user experience (UX) during e-commerce has been a relatively important research area especially in the last decade. The use of conventional methods in UX such as task-observation, in-depth interviews and questionnaires has already contributed for the measurement of the efficiency and effectiveness. This empirical study has aimed to make use of both conventional and neuroscientific methods simultaneously to provide a richer analysis framework for understanding the product search experience of the first-time buyers. The current work provides insights for the results from the combined use of conventional and neuroscientific-biometric methods in a UX study. Although this has been an exploratory study within a limited literature, the obtained results indicate a potential use of these methods for UX research, which may contribute to improve the relevant experience in various digital platforms.Patent Erasure Coding Magnetic Tapes for Minimum Latency and Adaptive Parity Protection Feedback(Patent Ofisi : US, 2019) Goker, Turguy; Arslan, Şuayb Şefik; Le, Hoa; Peng, James; Prigge, CarstenA magnetic tape device or system can store erasure encoded data that generates a multi-dimensional erasure code corresponding to an erasure encoded object comprising a code-word (CW). The multi-dimensional erasure code enables using a single magnetic tape in response to a random object/file request, and correct for an error within the single magnetic tape without using other tapes. Encoding logic can further utilize other magnetic tapes to generate additional parity tapes that recover data from an error of the single magnetic tape in response to the error satisfying a threshold severity for a reconstruction of the erasure coded object or chunk (s) of the CW. The encoding logic can be controlled, at least in part, by one or more iterative coding processes between multiple erasure code dimensions that are orthogonal to one another.Patent Network Attached Device for Accessing Removable Storage Media(Patent Ofisi : US, 2018) Goker, Turguy; Lee, Jaewook; Le, Hoa; Arslan, Şuayb Şefik; Peng, JamesEmbodiments disclosed herein provide systems, methods, and computer readable media to access data on removable storage media via a network attached access device. In a particular embodiment, a method provides receiving one or more user provided, in the removable storage media access device, receiving data over a packet communication network for storage on a removable storage medium. After receiving the data, the method provides preparing the data for storage on the removable storage medium. After preparing the data, the method provides writing the data to the removable storage medium.Conference Object Citation - WoS: 1Citation - Scopus: 1Hata Düzeltme Çıktı Kodları: Genel Bakış, Zorluklar ve Gelecek Yönelimler(IEEE, 2019) Arslan, Şuayb Şefik; Arslan, Şefik Şuayb; Güney, Osman B.; 02.02. Department of Computer Engineering; 02. Faculty of Engineering; 01. MEF UniversityÇok sınıflı sınıflandırma problemini çözmenin en etkili yollarından biri, bir grup akıllıca tasarlanmıs ikili sınıflandırıcı kullanarak, sınıflandırıcı sonuçlarını belli bir kritere göre bir araya getirmektir. Hata Düzeltme Çıktı Kodları (HDÇK) birden fazla ikili sınıflandırma yoluyla is bölümü saglayan basarılı tekniklerden biridir. Bu çalışmamızın amacı modern HDÇK tiplerine kısa bir giris yapmak, ikili sınıflandırma sonuçlarını birlestiren çesitli kod çözme yöntemleri ve zorlukları, avantajları ve dezavantajlarını ortaya koyan karsılastırmalı bir çalısma sunmaktır. Ayrıca HDÇK tekniğinin birkaç önemli uygulaması, MNIST veri seti üzerindeki performansı ve gelecekteki egilimlerin bazıları sunulmaktadır.Conference Object Citation - WoS: 9Citation - Scopus: 6Recognizing Non-Manual Signs in Turkish Sign Language(IEEE, 2019) Gökberk, Berk; Akarun, Lale; Aktaş, Müjde; 02.02. Department of Computer Engineering; 02. Faculty of Engineering; 01. MEF UniversityRecognition of non-manual components in sign language has been a neglected topic, partly due to the absence of annotated non-manual sign datasets. We have collected a dataset of videos with non-manual signs, displaying facial expressions and head movements and prepared frame-level annotations. In this paper, we present the Turkish Sign Language (TSL) non-manual signs dataset and provide a baseline system for non-manual sign recognition. A deep learning based recognition system is proposed, in which the pre-trained ResNet Convolutional Neural Network (CNN) is employed to recognize question, negation side to side and negation up-down, affirmation and pain movements and expressions. Our subject independent method achieves 78.49% overall frame-level accuracy on 483 TSL videos performed by six subjects, who are native TSL signers. Prediction results of consecutive frames are filtered for analyzing the qualitative results.Conference Object Citation - Scopus: 4Multi-View Reconstruction of 3d Human Pose With Procrustes Analysis(IEEE, 2019) Gökberk, Berk; Gökberk, Berk; Akarun, Lale; Temiz, Hüseyin; Gokherk, Berk; 02.02. Department of Computer Engineering; 02. Faculty of Engineering; 01. MEF UniversityRecovery of 3D human pose from cameras has been the subject of intensive research in the last decade. Algorithms that can estimate the 3D pose from a single image have been developed. At the same time, many camera environments have an array of cameras. In this paper, after aligning the poses obtained from single images using Procrustes Analysis, median filtering is utilized to eliminate outliers to find final reconstructed 3D body joint coordinates. Experiments performed on the CMU Panoptic, and Human3.6M databases demonstrate that the proposed system achieves accurate 3D body joint reconstructions. Additionally, we observe that camera selection is useful to decrease the system complexity while attaining the same level of reconstruction performance.Conference Object Citation - WoS: 2Citation - Scopus: 2Distributed Matrix Multiplication With Mds Array Bp-Xor Codes for Scaling Clusters(IEEE, 2019) Arslan, Şefik Şuayb; 02.02. Department of Computer Engineering; 02. Faculty of Engineering; 01. MEF UniversityThis study presents a novel coded computation technique for distributed matrix-matrix product computation at a massive scale that outperforms well known previous strategies in terms of total execution time. Our method achieves this performance by distributing the encoding operation over the cluster (slave) nodes at the expense of increased master-slave communication. The product computation is performed using MDS array Belief Propagation (BP)-decodable codes based on pure XOR operations. In addition, our scheme is configurable and suited for modern compute node architectures equipped with multiple processing units organized in a hierarchical manner. Assuming the number of backup nodes being sublinear in the size of the product, we shall demonstrate that the proposed scheme achieves order-optimal computation from an end-to-end latency perspective while ensuring acceptable communication requirements that can be addressed by today's high speed network link infrastructures.Conference Object Kernel Density Estimation for Optimal Detection in All-Bit Mlc Flash Memories(IEEE, 2019) Arslan, Şefik Şuayb; Ashraf, Reza A.; Pusane, Ali E.; Ashrafi, Reza A.; 02.02. Department of Computer Engineering; 02. Faculty of Engineering; 01. MEF UniversityNAND flash memories have recently become the main component of large-scale non-volatile storage systems. Recent studies have shown that various error sources degrade the Multi-level cell (MLC) memory performance, including intercell interference, retention error, and random telegraph noise. Accurate integration of these error sources into the analytical model to optimally derive the governing probability distributions and consequently the detection thresholds to minimize error rates lie at the heart of MLC research. Utilizing static derivations will not address the detection problem, as aforementioned error sources exhibit a strong non-stationary behavior. In this paper, a novel low-complexity implementation of a non-parametric learning mechanism, kernel density estimation, shall be used to periodically estimate the underlying probability distributions and hence approximate the optimal detection performance for time-varying all-bit-line MLC flash channel.Conference Object Citation - Scopus: 3An Xml Parser for Turkish Wikipedia(IEEE, 2019) Demir, Şeniz; Vardar, Uluç Furkan; Devran, İlkay Tevfik; 02.02. Department of Computer Engineering; 02. Faculty of Engineering; 01. MEF UniversityNowadays, visual and written data that can be easily accessed over the internet has enabled the development of research in many different fields. However, the availability of data is not sufficient by itself. It is of great importance that these data can be effectively utilized and interpreted in accordance with the requirements. Access to written content in the Wikipedia encyclopedia, which is becoming increasingly common in Turkish natural language processing, can be done via XML dumps. In this study, our aim is to develop and demonstrate the applicability of an XML parser for the processing of Turkish Wikipedia dumps. The use of the open-source parser, which allows information extraction at different levels of granularity, is reported on pages containing biography infoboxes and textual contents.