Abstract: A control system for a microscope having a sample stage for carrying an object, an imaging lens system for imaging the object and a digital capture unit for capturing the imaged object. The system provides a first operating mode wherein a user with first user rights can compile and define a work sequence for capturing the object and for evaluating the captures. The system or a first user can predefine which changes in the sequence and/or parameters influencing the sequence are possible, but a user with second user rights cannot. The system also provides a second operating mode in which a user with the second user rights can select and perform the defined work sequence. The control system enables the user with the second user rights to make changes in the sequence and/or of the parameters influencing the selected work sequence only within the predefined framework while blocking other changes.

Abstract: The invention relates to a method for microscopically examining a sample, wherein, in an overview mode, first an overview image of the sample composed of a large number of individual images is recorded through a microscope (20) followed by a transition to a detail mode, in which detail images of regions of interest of the sample are recorded through said microscope. The method is characterized in that the recording of the overview image in the overview mode is carried out at a lower resolution of the respectively used camera than that employed for the recording of the detail images and that the overview image and the detail images are recorded using the same microscope objective. Furthermore, the invention relates to a device for microscopically examining a sample, a computer program and a computer program product.

Abstract: A method is disclosed for generating an application that analyzes image data, such as from satellite and microscope pictures. The method uses a graphical user interface to add a new processing object to a processing object network. The processing object network includes a parent processing object and a child processing object. A user can append a new processing object to the child processing object or can add the new processing object as a subprocess to the parent processing object. The user selects a data domain and an algorithm from selection lists on the graphical user interface and adds them to the new processing object. The application uses a semantic cognition network to process data objects that are generated by segmenting the image data. The application then uses the new processing object to identify portions of the image that are to be highlighted on the graphical user interface.

Abstract: A method is disclosed for generating an application that analyzes image data, such as from satellite and microscope pictures. The method uses a graphical user interface to add a new processing object to a processing object network. The processing object network includes a parent processing object and a child processing object. A user can append a new processing object to the child processing object or can add the new processing object as a subprocess to the parent processing object. The user selects a data domain and an algorithm from selection lists on the graphical user interface and adds them to the new processing object. The application uses a semantic cognition network to process data objects that are generated by segmenting the image data. The application then uses the new processing object to identify portions of the image that are to be highlighted on the graphical user interface.

Abstract: A method is disclosed for extracting information from input data comprising mapping of the input data into a data object network. The method uses a semantic cognition network comprised of the data object network, a class object network and a processing object network. The semantic cognition network uses a set of algorithms to process the semantic units. The semantic cognition network defines a processing object in the processing object network by selecting a data domain in the data object network, a class domain in the class object network and an algorithm from the set of algorithms. The processing object comprises the data domain, the class domain and the algorithm. The processing object is used in the processing object network to process the semantic units.

Abstract: A method is disclosed for extracting information from input data comprising mapping of the input data into a data object network. The method uses a semantic cognition network comprised of the data object network, a class object network and a processing object network. The semantic cognition network uses a set of algorithms to process the semantic units. The semantic cognition network defines a processing object in the processing object network by selecting a data domain in the data object network, a class domain in the class object network and an algorithm from the set of algorithms. The processing object comprises the data domain, the class domain and the algorithm. The processing object is used in the processing object network to process the semantic units.