Titlebook: Semantic Networks for Understanding Scenes; Gerhard Sagerer,Heinrich Niemann Book 1997 Springer Science+Business Media New York 1997 algor

arrogant

Knowledge Representation, the storage of the entities of the aspects and levels as mentioned above. Especially the representation of constraints and associations between objects and events in the real world is necessary. This is also a reminiscent of Postulate 3 in section 1.1 where the existence of structure in a complex pattern was required.

外露

effrontery

Acquisition of Knowledge,e made on the acquisition of procedural knowledge. Often the term knowledge acquisition also refers to the interaction between a knowledge engineer and a domain expert in order to elicit the knowledge relevant for solving a particular problem. This important aspect is excluded here due to space limitations.

fulmination

Explanation and user Interface,system designer. A user interface should at least assist a person in using the system efficiently without reading extensive manuals. So the purpose of explanation and user interface is to make a complex system transparent and easy to use.

除草剂

Introduction,s to be a small open place between the group of houses in the foreground and the store in the background”. In such or a similar way the content of the natural scene shown above can be described. It is quite easy to give such a short description. The problem is somewhat more complex for the second im

粗鲁性质

Segmentation,heir relevant properties. It is beyond the scope of this volume to give a detailed and in depth treatment of segmentation. Rather, the purpose of this chapter is to show which types of results can be achieved by an initial phase of mainly bottom-up (or data-driven) processing using . knowledge, whic

Genistein

Knowledge Representation,shed three different aspects and five general levels of knowledge for the discussed context. Based on these distinctions and the proposed homogenous system architecture — see section 1.3 — this chapter will address the problem of knowledge representation. As a first-order approximation this requires

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