This paper presents an application of the general sample-to-object approach to the problem of invariant image classification. The approach results in defining new SVM kernels base...
In this paper, we study the classification problem involving information spanning multiple private databases. The privacy challenges lie in the facts that data cannot be collected...
An improved processing description to be employed in biosonar signal processing in a cochlea model is proposed and examined. It is compared to conventional models using a modified ...
The paper deals with the concept of relevance learning in learning vector quantization and classification. Recent machine learning approaches with the ability of metric adaptation...
Thomas Villmann, Frank-Michael Schleif, Barbara Ha...
We present a general method for explaining individual predictions of classification models. The method is based on fundamental concepts from coalitional game theory and prediction...