Recently CNN with nonlinear weight functions are used for various problems. Thereby nonlinear weights are represented by polynomials or tabulated functions combined with a cubic spline interpolation.
In this paper a linear interpolation technique is considered to allow an accurate approximation of nonlinear weight functions in CNN. In a previous publication the Table Minimising Algorithm (TMA) was introduced and applied to the Korteweg-de Vries-equation (KdV). In this contribution new results obtained by applying the algorithm to additional partial differential equations (PDE) will be given and discussed.
In this contribution new results in the field of video processing regarding the problem of obstacle detection will be presented.
Video sequences obtained from a camera mounted in a driving car are used as the input to a CNN and different templates are applied to extract multiple features from video sequences. Thereby, CNN with nonlinear weight functions have been considered allowing a reliable feature extraction. A detailed discussion of the algorithms and obtained results will be given in this paper.