Abstract: An event classification is trained by machine learning. An anomaly detection for detecting events in an image data set is thereby performed. Based on the performance of the anomaly detection, a model assumption of the event classification is determined. An image data set may include a plurality of images, and each image may include an array of pixels. Further, an image data set may include volume data and/or a time sequence of images and in this way represent a video sequence.

Abstract: An event classification is trained by machine learning. An anomaly detection for detecting events in an image data set is thereby performed. Based on the performance of the anomaly detection, a model assumption of the event classification is determined. An image data set may include a plurality of images, and each image may include an array of pixels. Further, an image data set may include volume data and/or a time sequence of images and in this way represent a video sequence.

Abstract: The invention is relates to a method of producing aryl-substituted, amino-acylated phosphonic-acid derivatives with the aid of metal complexes of chiral amphiphilic ligands in that according to the invention .alpha.-N-acyl-protected, .beta.-substituted alkene phosphone derivatives are asymmetrically hydrogenated in the presence of a chiral rhodium catalyst in a solvent or a suspension. The use of the micelle-forming catalyst makes possible the hydrogenation of unsaturated phosphonic-acid derivatives in water with a high reaction rate with the obtainment of very good enantiomeric excesses.