Yazar "0000-0002-7008-4778" için listeleme
-
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, ... -
Compression of ECG signals using variable-length classified vector sets and wavelet transforms
Gürkan, Hakan (Springer International Publishing AG, 2012)In this article, an improved and more efficient algorithm for the compression of the electrocardiogram (ECG) signals is presented, which combines the processes of modeling ECG signal by variable-length classified signature ... -
Compression of the CT images using classified energy and pattern blocks
Gökbay, İnci Zaim; Gezer, Murat; Güz, Ümit; Gürkan, Hakan; Yarman, Bekir Sıddık Binboğa (IEEE, 2013)In this work, a new biomedical image compression method is proposed based on the classified energy and pattern blocks (CEPB). CEPB based compression method is specifically applied on the Computed Tomography (CT) images and ... -
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 ... -
EEG signal compression based on classified signature and envelope vector sets
Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık Binboğa (IEEE Computer Society, 2007)In this paper, a novel method to compress ElectroEncephaloGram (EEG) Signal is proposed. The proposed method is based on the generation Classified Signature and Envelope Vector Sets (CSEVS) by using an effective k-means ... -
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 ... -
An efficient ECG data compression technique based on predefined signature and envelope vector banks
Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık Binboğa (IEEE, 2005)In this paper, a new method to compress ElectroCardioGram (ECG) Signal by means of "Predefined Signature and Envelope Vector Banks-PSEVB" is presented. In this work, on a frame basis, any ECG signal is modeled by multiplying ... -
Elektroensefalogram (EEG) işaretlerinin sıkıştırılmasında özgün bir yaklaşım
Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık Binboğa (IEEE, 2008)Bu çalışmada, Elektroensefalogram(EEG) işaretlerinin yeniden oluşturulmasına yönelik olarak yeni bir yöntem sunulmaktadır. Sunulan yöntem, etkin bir k-ortalamalı sınıflandırma algoritması kullanılarak Sınıflandırılmış Temel ... -
Extraction and comparison of various prosodic feature sets on sentence segmentation task for Turkish broadcast news data
Dalva, Doğan; Revidi, İzel D.; Güz, Ümit; Gürkan, Hakan (IEEE, 2014)In this work, prosodic features of the Turkish Broadcast News (BN) data are extracted using an open source prosodic feature extraction tool based on Praat. The profiles and effectiveness of these features are also investigated ... -
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 ... -
A new algorithm for high speed speech and audio coding
Güz, Ümit; Gürkan, Hakan; Yarman, Bekir Sıddık Binboğa (IEEE, 2007)In this work, a new mathematical modeling approach is proposed for the representation of the speech and audio signals. This approach is based on the generation of the so called Predefined Signature Sequence (PSS) and ... -
A new coding method for speech and audio signals
Güz, Ümit; Gürkan, Hakan; Yarman, Bekir Sıddık Binboğa (IEEE, 2005)In this paper a new representation or modeling method of speech signals is introduced. The proposed method is based on the generation of the so-called Predefined Signature S={S R } and Envelope vector E={E K } Sets (PSEVS). ... -
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 New speech coding algorithm using zero cross and phoneme based SYMPES
Şişman, Burak; Güz, Ümit; Gürkan, Hakan; Yarman, Bekir Sıddık Binboğa (IEEE, 2013-07-11)In this work, a new low bit rate hybrid speech coding approach which combines the benefits of the SYMPES (Systematic Procedure for Predefined Envelope and Signature Sequences) and zero cross and phoneme based segmentation ... -
A new speech modeling method: SYMPES
Güz, Ümit; Gürkan, Hakan; Yarman, Bekir Sıddık Binboğa (IEEE, 2006)In this paper, the new method of speech modeling which is called SYMPES is introduced and it is compared with the commercially available methods. It is shown that for the same compression ratio or better, SYMPES yields ... -
A novel biometric authentication approach using electrocardiogram signals
Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık Binboğa (IEEE, 2013)In this work, we present a novel biometric authentication approach based on combination of AC/DCT features, MFCC features, and QRS beat information of the ECG signals. The proposed approach is tested on a subset of 30 ... -
A novel computed tomography image compression method based on classified energy and pattern blocks
Gökbay, İnci Zaim; Gezer, Murat; Güz, Ümit; Gürkan, Hakan; Yarman, Bekir Sıddık Binboğa (IEEE, 2013)In this work, a new biomedical image compression method is proposed based on the classified energy and pattern blocks (CEPB). CEPB based compression method is specifically applied on the Computed Tomography (CT) images and ... -
A novel fast algorithm for speech and audio coding
Güz, Ümit; Gürkan, Hakan; Yarman, Bekir Sıddık Binboğa (IEEE, 2007)In this work a new mathematical modeling approach is proposed for the representation of the speech and audio signals. This approach is based on the generation of the so called Predefined Signature Sequence (PSS) and ... -
A novel human identification system based on electrocardiogram features
Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık Binboğa (IEEE, 2013)In this work, we present a novel biometric authentication approach based on combination of AC/DCT features, MFCC features, and QRS beat information of the ECG signals. The proposed approach is tested on a subset of 30 ...