In this paper, we propose a novel approach to address the problem of functional outlier detection. Our method leverages a low-dimensional and stable representation of functions using Reproducing Kernel Hilbert Spaces ...

We introduce the Integrated Dual Local Depth, which is a local depth measure for data in a Banach space based on the use of one-dimensional projections. The properties of a depth measure are analyzed under this setting and ...

The lens depth of a point has been recently extended to general metric spaces, which is not the case for most depths. It is defined as the probability of being included in the intersection of two random balls centred at ...

We present a generalized approach to obtain improved Raman intensity profiles from in-depth studies performed by confocal Raman microspectroscopy (CRM) with dry objectives. The approach is based on regularized deconvolution ...

In depth map generation, the settings of the algorithm parameters to yield an accurate disparity estimation are usually chosen empirically or based on unplanned experiments -- A structured statistical approach including ...

We herein introduce variable selection procedures based on depth similarity, aimed at identifying a small subset of variables that can better explain the depth assigned to each point in space. Our study is not intended to ...

Predictive models to estimate correlation coefficients between peak ground acceleration, peak ground velocity, and spectral acceleration residuals for Mexican intermediate-depth, intraslab earthquakes recorded on rock sites ...

Objectives: To compare simulated periodontal bone defect depth measured in digital radiographs with dedicated and non-dedicated software systems and to compare the depth measurements from each program with the measurements ...

Objectives: To compare simulated periodontal bone defect depth measured in digital radiographs with dedicated and non-dedicated software systems and to compare the depth measurements from each program with the measurements ...

This thesis proposes a versatile methodology for measuring, modeling, and predicting errors as the Root Mean Square Error (RMSE) in depth and the Relative Positioning Error (RPE) using data captured from an RGB-D camera ...