Yazar "Barkana, Atalay" için listeleme
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Application of Linear Regression Classification to low-dimensional datasets
Koç, Mehmet; Barkana, Atalay (Elsevier Science BV, 2014)The Traditional Linear Regression Classification (LRC) method fails when the number of data in the training set is greater than their dimensions. In this work, we proposed a new implementation of LRC to overcome this problem ... -
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 ... -
CNC-Tezgah Eğitiminin Bilgisayar programlarıyla yapılması
Seke, Erol (Anadolu Üniversitesi, 1988)Çalışmada, makine dili ve BASIC kullanılarak eğitim amaçlı bir CNCtorna tezgahı ile bir kişisel bilgisayar arasında iletişim kurmak ve CNC yazılımında eğitim amacı güdülmüştür. Öncelikle CNC-torna tezgahının mikrobilgisayarı ... -
The common vector approach and its comparison with other subspace methods in case of sufficient data
Gülmezoğlu, M. Bilginer; Dzhafarov, Vakif; Edizkan, Rıfat; Barkana, Atalay (Academic Press LTD- Elsevier Science LTD, 2007)This paper presents an application of the common vector approach (CVA), an approach mainly used for speech recognition problems when the number of data items exceeds the dimension of the feature vectors. The calculation ... -
The common vector approach and its relation to principal component analysis
The main point of the paper is to show the close relation between the nonzero principal components and the difference subspace together with the complementary close relation between the zero principal components and the ... -
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 ... -
Covariance analysis of voltage waveform signature for power-quality event classification
Gerek, Ömer Nezih; Ece, Doğan Gökhan; Barkana, Atalay (IEEE-Inst Electrical Electronics Engineers Inc, 2006)In this paper, covariance behavior of several features (signature identifiers) that are determined from the voltage waveform within a time window for power-quality (PQ) event detection and classification is analyzed. A ... -
Discriminative common vector approach based feature selection in face recognition
Koç, Mehmet; Barkana, Atalay (Pergamon-Elsevier Science LTD, 2014)A novel feature selection algorithm is proposed, which is related to the Discriminative Common Vector Approach (DCVA) utilized as a means to reduce the computational complexity of the facial recognition problem. The ... -
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 ... -
Face recognition using common matrix approach
In this paper, a new approach which is called the common matrix approach is proposed for face recognition. The common mat rix for each class can be calculated either using Gram-Schmidt orthogonalization method or using ... -
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 ... -
A fast method for the implementation of common vector approach
Koç, Mehmet; Barkana, Atalay; Gerek, Ömer Nezih (Elsevier Science Inc, 2010)In this paper a novel computation method is proposed to perform the common vector approach (CVA) faster than its conventional implementation in pattern recognition. While conventional CVA calculations perform the classification ... -
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 ... -
Kernel common vector method: A Novel nonlinear subspace classifier for pattern recognition
Çevikalp, Hakan; Nearntu, Marian; Barkana, Atalay (IEEE-Inst Electrical Electronics Engineers Inc, 2007)The common vector (CV) method is d linear subspace classifier method which allows one to discriminate between classes of data sets, such as those arising in image and word recognition. This method utilizes subspaces that ... -
Large margin classifiers based on affine hulls
Çevikalp, Hakan; Triggs, Bill; Yavuz, Hasan Serhan; Küçük, Yalçın; Küçük, Mahide; Barkana, Atalay (Elsevier Science BV, 2010)This paper introduces a geometrically inspired large margin classifier that can be a better alternative to the support vector machines (SVMs) for the classification problems with limited number of training samples. In ... -
Lineer olmayan sistemler ve en iyi salınım sinyali üzerine çalışmalar
Yaşar, Celal (Anadolu Üniversitesi, 1988)Lineer olmayan sistemlerin karakteristikleri genellikle lineer duruma getirilmek istenir. Bu sistemlerin karakteristiklerini lineer duruma getirmek için kullaılan metotlardan birisi sistemin giriş sinyaline salınım sinyali ... -
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 ...
