Yazar "0000-0002-4597-0954" için MF - Makale Koleksiyonu | Elektrik-Elektronik Mühendisliği Bölümü / Department of Electrical-Electronics Engineering listeleme
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Biometric identification using fingertip electrocardiogram signals
Güven, Gökhan; Gürkan, Hakan; Güz, Ümit (Springer London Ltd, 2018-07)In 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 ... -
Bürünsel, sözcüksel ve biçimbilgisel bilgiyi kullanan co-training ile Türkçe konuşma dilinin otomatik cümle bölütlemesi
Güz, Ümit; Gürkan, Hakan (Tübitak, 2015-04)Co-training, web sayfası sınıflandırması, kelime anlam açıklaştırma ve adlandırılmış varlık tanıma gibi pek çok sınıflandırma işlevinde başarı ile kullanılan oldukça etkili bir makine öğrenme algoritmasıdır. Co-training, ... -
Cascaded model adaptation for dialog act segmentation and tagging
Güz, Ümit; Tür, Gökhan; Hakkani Tür, Dilek; Cuendet, Sebastien (Elsevier Ltd, 2010-04)There are many speech and language processing problems which require cascaded classification tasks. While model adaptation has been shown to be useful in isolated speech and language processing tasks, it is not clear what ... -
Compression of the biomedical images using quadtree-based partitioned universally classified energy and pattern blocks
Gezer, Murat; Gargari, Sepideh Nahavandi; Güz, Ümit; Gürkan, Hakan (Springer London, 2019-03-15)In this work, an efficient low bit rate image coding/compression method based on the quadtree-based partitioned universally classified energy and pattern building blocks (QB-UCEPB) is introduced. The proposed method combines ... -
EEG signal compression based on classified signature and envelope vector sets
Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık Binboğa (Wiley, 2009-03)In this paper, a novel method to compress electroencephalogram (EEG) signal is proposed. The proposed method is based on the generation process of the classified signature and envelope vector sets (CSEVS), which employs ... -
Effective semi-supervised learning strategies for automatic sentence segmentation
Dalva, Doğan; Güz, Ümit; Gürkan, Hakan (Elsevier Science BV, 2018-04-01)The primary objective of sentence segmentation process is to determine the sentence boundaries of a stream of words output by the automatic speech recognizers. Statistical methods developed for sentence segmentation requires ... -
Generative and discriminative methods using morphological information for sentence segmentation of Turkish
Güz, Ümit; Favre, Benoit; Hakkani Tür, Dilek; Tür, Gökhan (IEEE-INST Electrical Electronics Engineers Inc, 2009-07)This paper presents novel methods for generative, discriminative, and hybrid sequence classification for segmentation of Turkish word sequences into sentences. In the literature, this task is generally solved using statistical ... -
Modeling of electrocardiogram signals using predefined signature and envelope vector sets
Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık Binboğa (Hindawi Publishing Corporation, 2007)A novel method is proposed to model ECG signals by means of "predefined signature and envelope vector sets (PSEVS)." On a frame basis, an ECG signal is reconstructed by multiplying three model parameters, namely, predefined ... -
Multi-view semi-supervised learning for dialog act segmentation of speech
Güz, Ümit; Cuendet, Sebastien; Hakkani Tür, Dilek; Tür, Gökhan (IEEE-INST Electrical Electronics Engineers Inc, 2010-02)Sentence segmentation of speech aims at determining sentence boundaries in a stream of words as output by the speech recognizer. Typically, statistical methods are used for sentence segmentation. However, they require ... -
A new method to represent speech signals via predefined signature and envelope sequences
Güz, Ümit; Gürkan, Hakan; Yarman, Bekir Sıddık Binboğa (Hindawi Publishing Corporation, 2007)A novel systematic procedure referred to as "SYMPES" to model speech signals is introduced. The structure of SYMPES is based on the creation of the so-called predefined "signature S = {S(R)(n)} and envelope E = {E(K) (n)}" ... -
A novel biometric identification system based on fingertip electrocardiogram and speech signals
Güven, Gökhan; Güz, Ümit; Gürkan, Hakan (Elsevier Inc., 2022-03)In this research work, we propose a one-dimensional Convolutional Neural Network (CNN) based biometric identification system that combines speech and ECG modalities. The aim is to find an effective identification strategy ... -
A novel image compression method based on classified energy and pattern building blocks
Güz, Ümit (Springer International Publishing AG, 2011)In this paper, a novel image compression method based on generation of the so-called classified energy and pattern blocks (CEPB) is introduced and evaluation results are presented. The CEPB is constructed using the training ... -
On the comparative results of "SYMPES: A new method of speech modeling"
Yarman, Bekir Sıddık Binboğa; Güz, Ümit; Gürkan, Hakan (Elsevier GMBH, 2006)In this paper, the new method of speech modeling which is called SYMPES (A Novel Systematic Procedure to Model Speech Signals via Predefined "Envelope and Signature Sequences") is introduced and it is compared with the ...