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Toplam kayıt 12, listelenen: 1-10
EEG signal compression based on classified signature and envelope vector sets
(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 ...
A novel image compression method based on classified energy and pattern building blocks
(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 ...
Generative and discriminative methods using morphological information for sentence segmentation of Turkish
(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 ...
A new method to represent speech signals via predefined signature and envelope sequences
(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)}" ...
Modeling of electrocardiogram signals using predefined signature and envelope vector sets
(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
(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 ...
Biometric identification using fingertip electrocardiogram signals
(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 ...
Effective semi-supervised learning strategies for automatic sentence segmentation
(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 ...
Compression of the biomedical images using quadtree-based partitioned universally classified energy and pattern blocks
(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 ...
A novel biometric identification system based on fingertip electrocardiogram and speech signals
(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 ...