Multiple classi"er fusion may generate more accurate classi"cation than each of the constituent classi"ers. Fusion is often based on "xed combination rules like the product and average. Only under strict probabilistic conditions can these rules be justi"ed. We present here a simple rule for adapting the class combiner to the application. c decision templates (one per class) are estimated with t...

The Z/2Z–graded intertwining operators are introduced. We study these operators in the case of “degenerate” N = 1 minimal models, with the central charge c = 3 2 . The corresponding fusion ring is isomorphic to the Grothendieck ring for the Lie superalgebra osp(1|2). We also discus multiplicity–2 fusion rules and logarithmic intertwiners.

This paper proposes a fusion model to reinforce fuzzy association rules, which contains two main procedures: (1) employing the cumulative probability distribution approach (CPDA) to partition the universe of discourse and build membership functions; and (2) using the AprioriTid mining algorithm to extract fuzzy association rules. The proposed model is more objective and reasonable in determinin...

Until now, of highest relevance for remote sensing data processing and analysis have been techniques for pixel level image fusion. So, This paper attempts to undertake the study of Feature-Level based image fusion. For this purpose, feature based fusion techniques, which are usually based on empirical or heuristic rules, are employed. Hence, in this paper we consider feature extraction (FE) for...

Building on the writings of Wittgenstein on rule-following and deviance, Kristóf Nyíri advanced a theory of creativity as consisting in a fusion of conflicting rules or disciplines. Only such fusion can produce something that is both intrinsically new and yet capable of being apprehended by and passed on to a wider community. Creativity, on this view, involves not the breaking of rules, or the ...

This paper presents two new promising combination rules for the fusion of uncertain and potentially highly conflicting sources of evidences in the theory of belief functions established first in Dempster-Shafer Theory (DST) and then recently extended in Dezert-Smarandache Theory (DSmT). Our work is to provide here new issues to palliate the well-known limitations of Dempster’s rule and to work ...

Axiomatic bases of admissible rules are obtained for fragments of the substructural logic R-mingle. In particular, it is shown that a “modus-ponens-like” rule introduced by Arnon Avron forms a basis for the admissible rules of its implication and implication-fusion fragments, while a basis for the admissible rules of the full multiplicative fragment requires an additional countably infinite set...

At present, fixed rules for classifier combination are the most used and widely investigated ones, while the study and application of trained rules has received much less attention. Therefore, pros and cons of fixed and trained rules are only partially known even if one focuses on crisp classifier outputs. In this paper, we report the results of an experimental comparison of well-known fixed an...

Many useful calculation rules, such as fusion and tupling, rely on well-structured functions, especially in terms of inputs and outputs. For instance, fusion requires that well-produced outputs should be connected to well-consumed inputs, so that unnecessary intermediate data structures can be eliminated. These calculation rules generally fail to work unless functions are well-structured. In th...

Ensemble is a representative technique for improving classification performance by combining a set of classifiers. It is required to maintain the diversity among base classifiers for effective ensemble. Conventional ensemble approaches construct various classifiers by estimating the similarity on the output patterns of them, and combine them with several fusion methods. Since they measure the s...