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Systematic Scale-Up of Mechanochemical Paracetamol-Oxalic Acid Cocrystal Synthesis across Multiple Milling Technologies. [PDF]
Org Process Res DevSchöbel JH, Gopinath D, Felderhoff M.
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Global patterns and inequalities in healthy aging: a multidimensional analysis using composite index and explainable AI. [PDF]
Front Public HealthÇelik S, Köroğlu CZ.
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The equivalence of two-dimensional PCA to line-based PCA
Pattern Recognition Letters, 2005The state-of-the-art in human face recognition is the subspace methods originated by the Principal Component Analysis (PCA), the Eigenfaces of the facial images. Recently, a technique called Two-dimensional PCA (2DPCA) was proposed for human face representation and recognition.
Liwei Wang, Jufu Feng
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SIAM Journal on Optimization, 2023
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Fatih S. Aktas, Mustafa Ç. Pinar
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fatih S. Aktas, Mustafa Ç. Pinar
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18th International Conference on Pattern Recognition (ICPR'06), 2006
In this paper, we first briefly reintroduce the 1D and 2D forms of the classical principal component analysis (PCA). Then, the PCA technique is further developed and extended to an arbitrary n-dimensional space. Analogous to 1D- and 2D-PCA, the new nD-PCA is applied directly to n-order tensors (n ges 3) rather than 1-order tensors (1D vectors) and 2 ...
Hongchuan Yu, Mohammed Bennamoun
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In this paper, we first briefly reintroduce the 1D and 2D forms of the classical principal component analysis (PCA). Then, the PCA technique is further developed and extended to an arbitrary n-dimensional space. Analogous to 1D- and 2D-PCA, the new nD-PCA is applied directly to n-order tensors (n ges 3) rather than 1-order tensors (1D vectors) and 2 ...
Hongchuan Yu, Mohammed Bennamoun
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2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE), 2020
Heart failure (HF) prediction is a challenging issue in medical informatics and is considered a deadliest disease worldwide. Recent research has been concentrated on features transformation and selection for improved HF prediction. In this study, we search optimal feature extraction algorithm by evaluating the performance of different feature ...
Atiqur Rehman +5 more
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Heart failure (HF) prediction is a challenging issue in medical informatics and is considered a deadliest disease worldwide. Recent research has been concentrated on features transformation and selection for improved HF prediction. In this study, we search optimal feature extraction algorithm by evaluating the performance of different feature ...
Atiqur Rehman +5 more
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Two-Dimensional Quaternion PCA and Sparse PCA
IEEE Transactions on Neural Networks and Learning Systems, 2019Benefited from quaternion representation that is able to encode the cross-channel correlation of color images, quaternion principle component analysis (QPCA) was proposed to extract features from color images while reducing the feature dimension. A quaternion covariance matrix (QCM) of input samples was constructed, and its eigenvectors were derived to
Xiaolin Xiao, Yicong Zhou
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