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Showing 1 to 5 of 5 for “"smoothing algorithms"”.

  1. Evaluating time-series smoothing algorithms for multi-temporal land cover classification

    … NDVI data to compare the capability of smoothing algorithms in noise reduction for improving land cover classification in the Great Lakes Basin, and providing groundwork to support cyanobacteria and cyanotoxin monitoring efforts. We used inter-class separability and intra-class …

    vt Repository record for Evaluating time-series smoothing algorithms for multi-temporal land cover classification (opens in a new tab)

  2. Methods of determining stream setback corridors in urban watersheds from remotely sensed data in the Dallas metropolitan area, Texas.

    … in areas of high relief, most likely due to the smoothing algorithms used in the post-processing of the raw LiDAR data, and field checking is advocated.

    baylor Repository record for Methods of determining stream setback corridors in urban watersheds from remotely sensed data in the Dallas metropolitan area, Texas. (opens in a new tab)

  3. Source localization of MEG generation using spatio-temporal Kalman filter

    … spatio-temporal Kalman filter and fixed-interval smoothing algorithms for MEG source localization.To compare the methods analytically, we present a Bayesian derivation of the regularized least squares and Kalman filtering methods. This analysis reveals that the estimates computed from the static …

    mit Repository record for Source localization of MEG generation using spatio-temporal Kalman filter (opens in a new tab)

  4. An Improved Algorithmic Approach to Iterative Floodway Modeling using HECRAS and GIS

    … on a DFIRM. We have developed automated mapping algorithms that accomplish this task. Some manual fine-tuning is required to finalize the floodway to be printed on FEMA's Flood Insurance Rate Maps (FIRMs).

    vt Repository record for An Improved Algorithmic Approach to Iterative Floodway Modeling using HECRAS and GIS (opens in a new tab)

  5. Improving the consistency of nonlinear estimators: analysis, algorithms, and applications

    … sensor observations. Even though many different algorithms, such as the extended Kalman filter (EKF) and the batch maximum a posteriori (MAP) estimator, have been developed for solving these problems, substantial empirical evidence shows that most existing nonlinear estimators tend to become …

    umn Repository record for Improving the consistency of nonlinear estimators: analysis, algorithms, and applications (opens in a new tab)