Results 21 to 30 of about 465,256 (146)
Fundus Image Classification Using VGG-19 Architecture with PCA and SVD
Symmetry, 2018 Automated medical image analysis is an emerging field of research that identifies the disease with the help of imaging technology. Diabetic retinopathy (DR) is a retinal disease that is diagnosed in diabetic patients.
M. Mateen +4 more
semanticscholar +1 more source
Robust Subspace Learning: Robust PCA, Robust Subspace Tracking, and Robust Subspace Recovery [PDF]
IEEE Signal Processing Magazine, 2017 Principal component analysis (PCA) is one of the most widely used dimension reduction techniques. A related easier problem is termed subspace learning or subspace estimation.
Namrata Vaswani +3 more
semanticscholar +1 more source
Potential Partnerships: Progressive Criminology, Grassroots Organizations and Social Justice
International Journal for Crime, Justice and Social Democracy, 2015 Criminologists around the globe are writing about the disproportionate criminalization of minority groups and – in the US in particular – about racial disproportionality in all aspects of the criminal justice system.
Tim Goddard +2 more
doaj +1 more source
A chemometric approach to the headspace sampled volatiles of selected Salvia species from Southeastern Serbia [PDF]
Botanica Serbica, 2022 Headspace sampling is a fast, simple and economical way to prepare plant samples for analysis by gas chromatography. For the first time, the composition of the head space volatiles (HSV) of six Salvia species (S. verticillata, S. glutinosa, S.
Emilija Kostić +5 more
doaj +1 more source
, 2018 Background The development of statistical software has enabled food scientists to perform a wide variety of mathematical/statistical analyses and solve problems.
D. Granato +4 more
semanticscholar +1 more source
Variational Autoencoders Pursue PCA Directions (by Accident) [PDF]
Computer Vision and Pattern Recognition, 2018 The Variational Autoencoder (VAE) is a powerful architecture capable of representation learning and generative modeling. When it comes to learning interpretable (disentangled) representations, VAE and its variants show unparalleled performance.
Michal Rolinek +2 more
semanticscholar +1 more source
Comparison of temporal and spatial patterns of water quality parameters in Anzali Wetland (southwest of the Caspian Sea) using Support vector machine model [PDF]
Caspian Journal of Environmental Sciences, 2021 Urgent is growing to have reliable information from the country's water resources. In recent years, data mining models such as artificial neural network (ANN), gene expression programming, Bayesian network, machine algorithms, such as a support vector ...
Maryam Fallah +3 more
doaj +1 more source
, 2021 Comparison of correct classification rate (CCR) [%] of each of MSM [12], the proposed 2D-PCA MSM, the proposed 2D-PCA-R MSM (θ = −10), and the proposed B-2D-PCA-R MSM on CASIA-C [14] (slow walk fs).
Yumi Iwashita (11261748) +3 more
core +1 more source
Scaled PCA: A New Approach to Dimension Reduction
Management Sciences, 2019 This paper proposes a novel supervised learning technique for forecasting: scaled principal component analysis (sPCA). The sPCA improves the traditional principal component analysis (PCA) by scaling each predictor with its predictive slope on the target ...
Da-Shan Huang +4 more
semanticscholar +1 more source
DWT/PCA face recognition using automatic coefficient selection [PDF]
, 2008 In PCA-based face recognition, there is often a trade-off between selecting the most relevant parts of a face image for recognition and not discarding information which may be useful.
Paul Nicholl +3 more
core +1 more source