Results 31 to 40 of about 27,772 (256)
IEEE Access, 2017 Since microaneurysms (MAs) can be seen as the earliest lesions in diabetic retinopathy, its detection plays a critical role in the diabetic retinopathy diagnosis.
Wei Zhou +4 more
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Craniofacial similarity analysis through sparse principal component analysis.
PLoS ONE, 2017 The computer-aided craniofacial reconstruction (CFR) technique has been widely used in the fields of criminal investigation, archaeology, anthropology and cosmetic surgery.
Junli Zhao +7 more
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Image Classification Based on Sparse Representation in the Quaternion Wavelet Domain
IEEE Access, 2022 In this study, we propose a novel sparse representation learning method in the Quaternion Wavelet (QW) domain for multi-class image classification. The proposed method takes advantages from: i) the QW decomposition, which promotes sparsity and provides ...
Long H. Ngo +4 more
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Extreme Learning Machine Based on Stacked Denoising Sparse Auto-Encoder [PDF]
Jisuanji gongcheng, 2020 Extreme Learning Machine(ELM)randomly selects input weights and hidden-layer bias of network,which increases the complexity and reduces the robustness of network.To address the problem,this paper proposes an ELM algorithm based on stacked Denoising ...
ZHANG Guoling, WANG Xiaodan, LI Rui, LAI Jie, XIANG Qian
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Model study of the leather degradation by oxidation and hydrolysis
Heritage Science, 2019 Many objects of culture heritage, comprised of leather, need to receive the right treatment to be restored and to elongate their lifespan. Determination of the degradation degree and even better the type of the degradation is a crucial knowledge for the ...
Gabriela Vyskočilová +4 more
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Characteristic gene selection via weighting principal components by singular values. [PDF]
PLoS ONE, 2012 Conventional gene selection methods based on principal component analysis (PCA) use only the first principal component (PC) of PCA or sparse PCA to select characteristic genes.
Jin-Xing Liu +4 more
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IET Radar, Sonar & Navigation, 2017 Microwave radar 3D imaging with high resolution generally requires a great number of samples. The authors aim at accurate reconstruction of microwave radar images while significantly reducing the required number of samples.
He Tian, Daojing Li
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Optimal Sparse Linear Auto-Encoders and Sparse PCA
CoRR, 2015 Principal components analysis (PCA) is the optimal linear auto-encoder of data, and it is often used to construct features. Enforcing sparsity on the principal components can promote better generalization, while improving the interpretability of the features. We study the problem of constructing optimal sparse linear auto-encoders.
Malik Magdon-Ismail, Christos Boutsidis
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SUPER-RESOLUTION OF HYPERSPECTRAL IMAGES USING COMPRESSIVE SENSING BASED APPROACH [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 Over the past decade hyper spectral (HS) image analysis has turned into one of the most powerful and growing technologies in the field of remote sensing.
R. C. Patel, M. V. Joshi
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On the Worst-Case Approximability of Sparse PCA
CoRR, 2015 20 ...
Siu On Chan +2 more
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