Results 121 to 130 of about 82,988 (261)
Asymptotically closer estimators for the normal covariance matrix
Journal of the Japan Statistical Society, Japanese Issue, 1984 Some estimators of a normal covariance matrix are compared based on the concept of asymptotic probability of closeness \((=APC)\). The estimators proposed by the author and \textit{M. Fujimoto} [Tsukuba J. Math. 6, 103-126 (1982; Zbl 0531.62054)] are shown to be asymptotically uniformly closer than \textit{L. R. Haff}'s estimator [Ann. Stat. 8, 586-597
openaire +2 more sources
Advanced Intelligent Discovery, EarlyView.Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto +3 more
wiley +1 more source
Channel Covariance Matrix Estimation via Dimension Reduction for Hybrid MIMO MmWave Communication Systems. [PDF]
Sensors (Basel), 2019 Hu R, Tong J, Xi J, Guo Q, Yu Y.
europepmc +1 more source
Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
Advanced Intelligent Discovery, EarlyView.Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong +5 more
wiley +1 more source
Covariance Matrix Estimation for the Cryo-EM Heterogeneity Problem. [PDF]
SIAM J Imaging Sci, 2015 Katsevich E, Katsevich A, Singer A.
europepmc +1 more source
Advanced Intelligent Discovery, EarlyView.AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia +2 more
wiley +1 more source
A Critical Assessment of Bonding Descriptors for Predicting Materials Properties
Advanced Intelligent Discovery, EarlyView.The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik +6 more
wiley +1 more source
A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design
Advanced Intelligent Discovery, EarlyView.Active learning (AL) strategies are benchmarked for the binary design of planar multilayer nanophotonic structures. Factorization machines combined with quantum annealing (QA) become effective as dimensionality increases. Hybrid QA provides the strongest results for 100‐layer problems, highlighting the importance of optimization method selection in ...
Serang Jung +10 more
wiley +1 more source
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.A laser pointer‐guided robotic grasping method for arbitrary objects based on promptable segment anything model and force‐closure analysis is presented. Grasp generation methods based on force‐closure analysis can calculate the optimal grasps for objects through their appearances. However, the limited visual perception ability makes robots difficult to
Yan Liu +5 more
wiley +1 more source
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.It is a fact that slippage causes tracking errors in both longitudinal and lateral directions which results to have less travel distance in tracking a reference trajectory. Less travel distance means having energy loss of the battery and carrying loads less than planned.
Gokhan Bayar +2 more
wiley +1 more source