Abstract: A method for the use of fractal semantic networks is disclosed, wherein the fractal semantic network contains both semantic units that possess respective information contents as well as link units that describe a relation content that respectively links two semantic units such that the mutual relationship of the two linked semantic units is determined through the relation content. In that case, a knowledge network consists of category units and, as the case may be, additionally of instance units and/or Janus units. For the querying of information, classification and/or selecting of semantic sub-networks in this knowledge network, the networking of semantic units taking into consideration the type, content, composition and/or distance of other semantic units in the respective network environment can be employed. Furthermore, Janus functionality can be employed for the local classification or for the local alteration of the networking of a semantic unit.

Abstract: A method for processing data structures with the aid of networked semantic units includes: acquiring a data structure, and generating, modifying, deleting and storing semantic structure units and networking them on the basis of the acquired data structure while using a knowledge base comprised of a network of semantic knowledge units. Semantic structure units and their network are classified in iterative steps. Based on this classification, a specific processing is activated which modifies a respective semantic structure unit and a particular partial network.

Abstract: A method for processing data structures with the aid of networked semantic units. The method includes acquiring a data structure, and generating, modifying, deleting and/storing semantic structure units and/networking them on the basis of the acquired data structure. The method uses a knowledge base comprised of a network of semantic knowledge units. Semantic structure units and/their network are classified in iterative steps. Based on this classification, a specific processing is activated which modifies a respective semantic structure unit and/a particular partial network.

Abstract: A method for processing data structures with the aid of networked semantic units includes: acquiring a data structure, and generating, modifying, deleting and storing semantic structure units and networking them on the basis of the acquired data structure while using a knowledge base comprised of a network of semantic knowledge units. Semantic structure units and their network are classified in iterative steps. Based on this classification, a specific processing is activated which modifies a respective semantic structure unit and a particular partial network.

Abstract: The present invention relates to a method for segmentation of a digital picture consisting of a multiplicity of single picture elements comprising determining if one of one and several features relating to contiguous picture objects comprising picture elements and picture segments are conforming or not conforming based on a specific homogeneity criterion by means of referencing a predetermined tolerance for each feature as a termination criterion, within which feature values relating to the contiguous picture objects in question may differ; if one of one feature and several features relating to the contiguous picture objects are determined to be conforming then merging the conforming picture objects; and repeating the resulting segmentation until the resulting segmentation converges in a stable or approximately stable condition in which no further contiguous picture objects are determined to be conforming.

Abstract: A method for fractal-darwinian object generation consists of the steps of: preparing a fractal object library including predetermined objects and associated rules of property and context, forming objects and comparing the formed objects with the objects in the fractal object library. By using the property rules, a local classification likelihood is allocated to each formed object. Thereupon, by using the context rules for each object, a respective fractal classification likelihood is formed. For optimisation of the fractal classification likelihood, alteration rules are applied to the objects. The above method is carried out iteratively, whereby a process of gradual optimisation takes place.

Abstract: What is disclosed is a method for processing data structures with the aid of networked semantic units, which comprises the steps of acquiring a data structure; and generating, modifying, deleting and/or storing semantic structure units and/or networking them on the basis of the acquired data structure while using a knowledge base comprised of a network of semantic knowledge units. Herein semantic structure units and/or their network are classified in iterative steps, and based on this classification a specific processing may be activated which modifies a respective semantic structure unit and/or a particular partial network.

Abstract: A fractal network for handling complex structures is disclosed, which is comprised of a multiplicity of units. The fractal network contains both semantic units each possessing informational contents and linking units describing a relational content. The relational content links two respective semantic units in such a manner that the mutual relation of the two linked semantic units is determined by the relational content.

Abstract: The present invention relates to a method for segmentation of a digital picture consisting of a multiplicity of single picture elements comprising determining if one of one and several features relating to contiguous picture objects comprising picture elements and picture segments are conforming or not conforming based on a specific homogeneity criterion by means of referencing a predetermined tolerance for each feature as a termination criterion, within which feature values relating to the contiguous picture objects in question may differ; if one of one feature and several features relating to the contiguous picture objects are determined to be conforming then merging the conforming picture objects; and repeating the resulting segmentation until the resulting segmentation converges in a stable or approximately stable condition in which no further contiguous picture objects are determined to be conforming.