Realistic virtual models of leaf surfaces are important for several applications in the plant
sciences, such as modelling agrichemical spray droplet movement and spreading on the …

Diese Arbeit beschäftigt sich mit einem neuen Ansatz für das Klassifikationsproblem beim
Maschinellen Lernen durch Funktionsrekonstruktion. Es basiert auf dem Zugang des …

The thin plate spline smoother is a classical model for finding a smooth function from the
knowledge of its observation at scattered locations which may have random noises. We …

The foliage of a plant performs vital functions. As such, leaf models are required to be
developed for modeling the plant architecture from a set of scattered data captured using a …

We consider a mixed finite element method for a linear multivariate spline using the
Laplacian penalty. Our discretisation is based on biorthogonal systems leading to a very …

The thin plate spline smoother is a data fitting and smoothing technique that captures
important patterns of potentially noisy data. However, it is computationally expensive for …

We present a new technique for solving the saddle point problem arising from a finite
element based thin plate spline formulation. The solver uses the Sherman–Morrison …

The finite element method has become a very powerful and popular tool to solve boundary
value problems coming from science and engineering. Here, we consider a scattered data …

Traditional thin plate splines use radial basis functions and require the solution of a dense
linear system of equations whose size is proportional to the number of data points. Instead of …

The thin plate spline, as introduced by Duchon, interpolates a smooth surface through
scattered data. It is computationally expensive when there are many data points. The finite …