Modern airborne synthetic aperture radar sensors provide high spatial resolution data. Experimental systems have even achieved decimetre resolution. In such data, many features of urban objects can be identified, which are beyond what has been achieved by radar remote sensing before. An example for the new quality of the appearance of urban man-made objects such as buildings in these data is gi...

We study the problem of recognizing a string Y which is the noisy version of some unknown string X* chosen from a finite dictionary, H. The traditional case which has been extensively studied in the literature is the one in which Y contains substitution, insertion and deletion (SID) errors. Although some work has been done to extend the traditional set of edit operations to include the straight...

Finite structures such as point patterns, strings, trees, and graphs occur as ”natural” representations of structured data in different application areas of machine learning. We develop the theory of structure spaces and derive geometrical and analytical concepts such as the angle between structures and the derivative of functions on structures. In particular, we show that the gradient of a dif...

A new method for shape learning is presented in this paper. This method incorporates abilities from both statistical and structural pattern recognition approaches to shape analysis. It borrows from statistical pattern recognition the capability of modelling sets of point coordinates, and from structural pattern recognition the ability of dealing with highly irregular patterns, such as those gen...

This panel deals with the relationships between artificial intelligence and pattern recognition. It addresses such issues as: How do the fields differ? How should they relate to one another? In particular, does AI have anything to learn from PR? Pattern recognition, classically, involves the extraction of features and their subsequent analysis in feature space using statistical tools or cluster...

We introduce special k-head finite array automata, which characterize the array languages generated by specific variants of regulated n-dimensional context-free array grammars of finite index we introduced in the first part of this paper. As a practical application we show how these analyzing devices in the two-dimensional case can be used in the field of syntactic character recognition. 1 Brid...

Chaudhari S. R. ,Komejwar D. D. , On Fuzzy Pushdown Automata and their covering , International Journal of Computer Applications Vol. 46(8),2012 pp 27-33 Comon H. ,Dauchet M. ,Gilleron R. ,Jacquemard F. , Lugiez D. ,Loding C. ,Tison S. , and Tommasi M. , Tree Automata: techniques and apllications. (2007) Lee E. T. Fuzzy tree automata and syntactic pattern recognition, IEEE Trans Pattern Anal Ma...

Vector quantization(VQ) is a lossy data compression technique from signal processing, which is restricted to feature vectors and therefore inapplicable for combinatorial structures. This contribution aims at extending VQ to the quantization of graphs in a theoretically principled way in order to overcome practical limitations known in the context of prototype-based clustering of graphs. For thi...

A method for the automatic location of phonetically important events in continuous speech signals is presented. The events chosen are plosive bursts, fricatives, nasals and vocalic onsets and offsets. These events have been chosen to match the requirements of a system that enhances these regions to make the signal more robust to channel degradation. The technique uses a syntactic pattern recogn...

A common way of expressing string similarity in structural pattern recognition is the edit distance. It allows one to apply the kNN rule in order to classify a set of strings. However, compared to the wide range of elaborated classifiers known from statistical pattern recognition, this is only a very basic method. In the present paper we propose a method for transforming strings into n-dimensio...