Results 21 to 30 of about 13,178 (146)

k-Covariance: An Approach of Ensemble Covariance Estimation and Undersampling to Stabilize the Covariance Matrix in the Global Minimum Variance Portfolio

Applied Sciences, 2022
A covariance matrix is an important parameter in many computational applications, such as quantitative trading. Recently, a global minimum variance portfolio received great attention due to its performance after the 2007–2008 financial crisis, and this ...
Tuan Tran, Nhat Nguyen, Trung Nguyen
doaj   +1 more source

Uncalibrated Distortions vs Undersampling

Vision Research, 1996
In a recent paper of ours [Hess & Field (1993). Vision Research, 33, 2663-2670], we claim that there was a predictable relationship between position errors and contrast errors for an undersampled system. In this paper we re-state our main points. We feel that the response to that paper by Levi and Klein in the accompanying article does not require us ...
FIELD, DAVID J, HESS, ROBERT F
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Universal Undersampled MRI Reconstruction [PDF]

, 2021
Deep neural networks have been extensively studied for undersampled MRI reconstruction. While achieving state-of-the-art performance, they are trained and deployed specifically for one anatomy with limited generalization ability to another anatomy.
Xinwen Liu, Jing Wang, Feng Liu, S. Kevin Zhou   +3 more
openaire   +2 more sources

Evaluating Landslide Susceptibility Using Sampling Methodology and Multiple Machine Learning Models

ISPRS International Journal of Geo-Information, 2023
Landslide susceptibility assessment (LSA) based on machine learning methods has been widely used in landslide geological hazard management and research.
Yingze Song, Degang Yang, Weicheng Wu, Xin Zhang, Jie Zhou, Zhaoxu Tian, Chencan Wang, Yingxu Song   +7 more
doaj   +1 more source

Selecting the Suitable Resampling Strategy for Imbalanced Data Classification Regarding Dataset Properties. An Approach Based on Association Models

Applied Sciences, 2021
In many application domains such as medicine, information retrieval, cybersecurity, social media, etc., datasets used for inducing classification models often have an unequal distribution of the instances of each class.
Mohamed S. Kraiem, Fernando Sánchez-Hernández, María N. Moreno-García   +2 more
doaj   +1 more source

Phase-contrast with interleaved undersampled projections [PDF]

Magnetic Resonance in Medicine, 2000
MR phase-contrast techniques provide velocity-sensitive angiograms and quantitative flow measurements but require long scan times. Recently it has been shown that undersampled projection reconstruction can acquire higher resolution per unit time than Fourier techniques with acceptable artifacts when used in contrast-enhanced MR angiography ...
A V, Barger, D C, Peters, W F, Block, K K, Vigen, F R, Korosec, T M, Grist, C A, Mistretta   +6 more
openaire   +2 more sources

Utilizing logistic regression to compare risk factors in disease modeling with imbalanced data: a case study in vitamin D and cancer incidence

Frontiers in Oncology, 2023
Imbalanced data, a common challenge encountered in statistical analyses of clinical trial datasets and disease modeling, refers to the scenario where one class significantly outnumbers the other in a binary classification problem. This imbalance can lead
Mohammad Meysami, Vijay Kumar, McKayah Pugh, Samuel Thomas Lowery, Shantanu Sur, Sumona Mondal, James M. Greene   +6 more
doaj   +1 more source

Beyond Nyquist: A Comparative Analysis of 3D Deep Learning Models Enhancing MRI Resolution

Journal of Imaging
High-spatial resolution MRI produces abundant structural information, enabling highly accurate clinical diagnosis and image-guided therapeutics. However, the acquisition of high-spatial resolution MRI data typically can come at the expense of less ...
Soumick Chatterjee, Alessandro Sciarra, Max Dünnwald, Anitha Bhat Talagini Ashoka, Mayura Gurjar Cheepinahalli Vasudeva, Shudarsan Saravanan, Venkatesh Thirugnana Sambandham, Pavan Tummala, Steffen Oeltze-Jafra, Oliver Speck, Andreas Nürnberger   +10 more
doaj   +1 more source

Phase-synchronous undersampling in nonlinear spectroscopy [PDF]

Optics Letters, 2018
We introduce the concept of phase-synchronous undersampling in nonlinear spectroscopy. The respective theory is presented and validated experimentally in a phase-modulated quantum beat experiment by sampling high phase modulation frequencies with low laser repetition rates.
Lukas Bruder, Marcel Binz, Frank Stienkemeier   +2 more
openaire   +5 more sources

Undersampled Windowed Exponentials and Their Applications [PDF]

Acta Applicandae Mathematicae, 2018
Referees comment incorporated, To appear in Acta.
Chun-Kit Lai, Sui Tang
openaire   +3 more sources