Another advantage is that these methods contain a probabilistic estimate of the interpolation quality itself (Burrough and McDonnell, 1998). When data sampling is sparse, it is crucial to adequately ...

(1) The proposed Unsupervised Interpolation Recovery Method and established data set effectively address the issues of over-recovery and large-scale reconstruction error, and improve the anomaly ...

Other interpolation methods can be requested. Note that interpolating values of a time series does not add any real information to the data as the interpolation process is not the same process that ...

In the work reported here, the authors use advanced deep learning algorithms to find a method of frame interpolation for coronary angiography videos that reduces the frequency of X-ray exposure by ...

Data-driven RRAM device models using Kriging interpolation Researchers propose a two-tier Kriging/GPR approach for modeling jump tables of RRAM devices and tests it comparatively to the traditional ...