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Toplam kayıt 31, listelenen: 21-30
A novel hybrid electrocardiogram signal compression algorithm with low bit-rate
(Springer, 2010)
In this paper, a novel hybrid Electrocardiogram (ECG) signal compression algorithm based on the generation process of the Variable-Length Classified Signature and Envelope Vector Sets (VL-CSEVS) is proposed. Assessment ...
Elektroensefalogram (EEG) işaretlerinin sıkıştırılmasında özgün bir yaklaşım
(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 ...
Model adaptation for dialog act tagging
(IEEE, 2006)
In this paper, we analyze the effect of model adaptation for dialog act tagging. The goal of adaptation is to improve the performance of the tagger using out-of-domain data or models. Dialog act tagging aims to provide a ...
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 new coding method for speech and audio signals
(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 novel representation method for electromyogram (EMG) signal with predefined signature and envelope functional bank
(IEEE, 2004)
In this paper, a new method to model EMG signals by means of "Predefined Signature and Envelope Functional Banks (PSEB)" is presented. Since EMG signals present quasi-stationary behavior, any EMG signal Xi is modeled by ...
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 ...
On the comparative results of "SYMPES: A new method of speech modeling"
(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 ...
Cascaded model adaptation for dialog act segmentation and tagging
(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 ...
Extension of conventional co-training learning strategies to three-view and committee-based learning strategies for effective automatic sentence segmentation
(IEEE, 2018)
The objective of this work is to develop effective multi-view semi-supervised machine learning strategies for sentence boundary classification problem when only small sets of sentence boundary labeled data are available. ...