Yazar "Barkana, Atalay" için Bildiri Koleksiyonu listeleme
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Application of the discriminative common vector approach to one sample problem [Ayirtedi·ci· ortak vektör yaklaşiminin tek örnek problemi·ne uygulanmasi]
Koç, Mehmet; Barkana, Atalay (2012)Matrix-based (2D) methods have advantages over vector-based (1D) methods. Matrix-based methods generally have less computational costs and higher recognition performances with respect to vector-based variants. In this work ... -
A comparison of the Common Vector and the discriminative Common Vector methods for face recognition
Çevikalp, Hakan; Barkana, B.; Barkana, Atalay (2005)The Common Vector (CV) method is a successful method which has been originally proposed for isolated word recognition problems in the case where the number of samples for each class is less than or equal to the dimensionality ... -
Endpoint detection of isolated words using center of gravity method
Gülmezoğlu, M. Bilginer; Edizkan, Rifat; Ergin, Semih; Barkana, Atalay (IEEE, 2007)In this study, center of gravity (COG) method is proposed to detect endpoints of isolated words. Common vector approach (CVA) is employed to evaluate the effect of the proposed method in the isolated word recognition. Since ... -
Endpoint detection of isolated words using center of gravity method [Agirlik merkezi yöntemini kullanarak yalitik kelimelerin uç noktalarinin belirlenmesi]
In this study, center of gravity (COG) method is proposed to detect endpoints of isolated words. Common vector approach (CVA) is employed to evaluate the effect of the proposed method in the isolated word recognition. Since ... -
A Fast Method for the Common Vector Approach
Koç, Mehmet; Barkana, Atalay (IEEE, 2009)In this paper a new method is proposed to perform the Common Vector Approach(CVA). While CVA performs the classification with respect to the distance between vectors, the new method performs the classification with respect ... -
A fast method for the common vector approach [Ortak vektör yaklaşimi i·çin hizli bir yöntem]
Koç, Mehmet; Barkana, Atalay (2009)In this paper a new method is proposed to perform the Common Vector Approach(CVA). While CVA performs the classification with respect to the distance between vectors, the new method performs the classification with respect ... -
Improvements on common vector approach for multi class problems
In multi-class problems, within- and between-class scatters should be considered in classification criterion. The common vector approach (CVA) uses the discriminative information obtained from within-class scatter of any ... -
Improvements on isolated word recognition using FLDA [FLDA kullanarak ayrik kelime tanimada yapilan iyileştirmeler]
The purpose of this study is to increase the recognition rates of the isolated word using improved Fisher's Linear Discriminant Analysis (FLDA). Therefore, at first, unique subspace for each class is constructed by defining ... -
Modular Common Vector Approach
Koç, Mehmet; Barkana, Atalay (IEEE, 2014)The performance of a face recognition system is negatively affected by the accessories used on the face Like many methods, the recognition performance of the Common Vector Approach (CVA) [1] over occluded images is not at ... -
Modular common vector approach [Modüler ortak vektör yaklaşimi]
Koç, Mehmet; Barkana, Atalay (IEEE Computer Society, 2014)The performance of a face recognition system is negatively affected by the accessories used on the face. Like many methods, the recognition performance of the Common Vector Approach (CVA) [1] over occluded images is not ... -
ORTAK VEKTÖR VE AYIRTEDİCİ ORTAK VEKTÖR YAKLAŞIMLARI İLE ÖZNİTELİK SEÇİMİ YÖNTEMİ
Koç, Mehmet; Barkana, Atalay (2011)Gerçek zamanlı yüz tanıma uygulamaları için öznitelik vektörü boyutu çok önemlidir. Yüksek boyutlu öznitelik vektörleri yüz tanıma sisteminin hesaplama karmaşıklığını ve yürütüm süresini arttırmaktadır. Bu çalışmada, ... -
Two dimensional (2D) subspace classifiers for image recognition
The Class-Featuring Information Compression (CLAFIC) is a pattern classification method which uses a linear subspace for each class. In order to apply the CLAFIC method to image recognition problems, 2D image matrices must ... -
Two-dimensional CLAFIC methods for image recognition [Görüntü tanimada i·ki boyutlu CLAFIC yöntemleri]
In this paper, we propose two variations of vector based class-featuring information compression (CLAFIC) methods which can be applied directly to the gray level digital image data. In these methods, gray level digital ... -
Voltage waveform pattern selection for power quality event classification
Gerek, Ömer Nezih; Ece, D. Gökhan; Barkana, Atalay (IEEE, 2007)Selection of useful and appropriate identifiers plays an important role in most detection and classification problems including the analysis of voltage waveform for power quality (PQ). In this case, the identifiers are ...