Titlebook: Geographic Information Science; 5th International Co Thomas J. Cova,Harvey J. Miller,Michael F. Goodchi Conference proceedings 2008 The Edi

Explosive

https://doi.org/10.1007/978-3-642-50916-2ar when it comes to the logical properties of the involved relations. Class relations are defined whenever the semantics of entire classes are described, independently of single instances. Typical examples are spatial semantic integrity constraints or ontologies of entity classes. The paper continue

NIB

,Die Untersuchung der Legierungsst?hle, as maps or non-maps by comparing them to previously classified map and non-map images using methods from Content-Based Image Retrieval (CBIR). Our approach outperforms the accuracy of the previous approach by 20% in F.-measure. Further, our method is more scalable and less costly than previous appr

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Die Praxis des Eisenhüttenchemikersquired computations. The imprecise positions produced using these inaccurate measurements mean that available methods for measurement of distances or angles are unsuitable for use in most applications. In this paper we present a new approach, the Anomaly Correction in Localization (ACL) algorithm, w

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開始發(fā)作

Das Schiedsgerichtswesen im Getreidehandel,. In order to define affordances in such a way that they can be used for classifying and describing instances in a geographic database, one has to deal with the problems of informational incompleteness and limited definability. In this paper, we propose an affordance-based theory of channel networks

CURB

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Refining Topological Relations between Regions Considering Their Shapes,n styles. In this paper, we present the ..., which refines topological relations into . by considering projective properties of the objects’ shapes. This is indeed a reformulation of projective concepts of the . within the framework of the .... Thirty projective binary relationsare established betwe

Synchronism

Noisy Road Network Matching,her, but with .′???.. We assume that . and . use different coordinate systems at (possibly) different, but known scales. Let . and . denote sets of ”prominent” road points (e.g., intersections) associated with . and ., respectively. The positions of road points on both sets may contain a certain amo

KEGEL

Extort

Uncovering Hidden Spatial Patterns by Hidden Markov Model,clidean distance has weaknesses. These include providing an over simplified representation of spatial dependence, being limited to certain spatial pattern and symmetrical relationships, being unable to account for cross-class dependencies, and unable to work with categorical especially multinomial d