Results 231 to 240 of about 7,844,010 (281)

Confidence-aware pseudo-label selection and verifier training for semi-supervised LLM reasoning with minimal labels. [PDF]

Front Artif Intell
Kato K, Chu C, Murawaki Y, Kurohashi S.
europepmc   +1 more source

FOR: Point Cloud Outlier Removal Based on Fuzzy Theory and Informativeness and Its Application to 3D Object Detection. [PDF]

Sensors (Basel)
Gan L, Yang Z, Liu Y, Wang Y, An X.
europepmc   +1 more source

Optimal Sequential Fusion Kalman Filter for Multi-Sensor Linear Systems with Noise Cross-Correlated. [PDF]

Sensors (Basel)
Huang W, Wen C.
europepmc   +1 more source

Fault Detection and Isolation of MEMS IMU Array Based on WOA-MVMD-GLT. [PDF]

Micromachines (Basel)
Li H, Sun F, Tian J, He X, Zhu T.
europepmc   +1 more source

Multi-Target Behavior and Intent Prediction Under Incomplete Perception. [PDF]

Sensors (Basel)
Ma Y, Han Y, Zhang X, Ping P.
europepmc   +1 more source

When high accuracy misleads in literature-derived machine learning for deep eutectic solvent recommendation. [PDF]

RSC Adv
Faraji H, Mendez-Perez JA, Rodríguez-Ramos R, Socas-Rodríguez B, Herrera Herrera AV.   +4 more
europepmc   +1 more source

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Sensor placement in optimal filtering and smoothing problems

IEEE Transactions on Automatic Control, 1982
The problem of sensor placement for optimal filtering and smoothing problems is considered. Matrix equations are derived that relate individual changes in sensor locations to changes in the covariance matrix. These gradient matrices are used in formulating a design procedure that seeks the optimal sensor location for a particular estimation problem ...
A Arbel
exaly   +3 more sources

Designing Optimal Spectral Filters for Inverse Problems

SIAM Journal on Scientific Computing, 2011
Summary: Spectral filtering suppresses the amplification of errors when computing solutions to ill-posed inverse problems; however, selecting good regularization parameters is often expensive. In many applications, data are available from calibration experiments. In this paper, we describe how to use such data to precompute optimal spectral filters. We
Julianne Chung, Matthias Chung, Dianne P. O'Leary   +2 more
openaire   +3 more sources

Exact and Approximate Algorithms for the Filter Design Optimization Problem

IEEE Transactions on Signal Processing, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Levent Aksoy, Paulo F. Flores, José Monteiro 0001   +2 more
openaire   +1 more source