Representation Archives

Discovered by accident

Some discoveries are made by accident. The wrong road brought a beautiful view. An arbitrary book from the library gave a great, new insight. A procedure was suddenly understood in a discussion with colleagues during a poster session. In a physical experiment a failure in controlling the circumstances showed a surprising phenomenon. Children playing with…

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Aristotle and the ugly duckling theorem

We already discussed several times the significance of understanding the Platonic and Aristotelian ways of gaining knowledge. It can be of great help to researchers in the field of pattern recognition in the appreciation of contributions by others, in discussions with colleagues and in supervising students. This may hold for science in general, but it…

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The ten Aristotelian categories, features and dissimilarities

The founding fathers of philosophy, Plato and Aristotle, created two competing foundations for knowledge: the ideas and the categories. According to Plato reality is constituted by the non-materialistic ideas: they are the true objects of the world. In his view ideas can be grouped into more and more universal ideas. According to Aristotle there is…

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Are the evaluation results of the new procedure you worked on for months, worse or at most marginally better than the baseline procedure? Don’t worry, it happens all the time. Are they surprisingly good? Congratulations! You may write an interesting paper. But can you really understand why they are so good? Check, check, and double-check….

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Good recognition is non-metric: true or false?

If the relations between the objects to be recognized are non-metric, there seems to be something wrong. However, Walter Scheirer and his co-authors claim in the  August issue of Pattern Recognition that “Good recognition is non-metric“, [1]:  Is this statement true or false? See also one of the webpages of Walter Scheirer. Readers of this…

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The Eurovision Song Contest Analyzed

The results of the 2014 Eurovision Song Festival may be of interest from a number of perspectives, e.g. artistic, political and cultural. Here I will focus on the last point and show how by simple pattern recognition tools the cultural similarities between the participating countries can be analyzed. At the end it will be discussed…

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Regularization and invariants

Regularization is frequently used in statistics and machine learning to stabilize sensitive procedures in case of insufficient data.. It will be argued here that it is specifically of interest in pattern recognition applications if it can be related to invariants of the specific problem at hand. It is thereby a means to incorporate prior knowledge…

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Random Representations

The goal of representation is in pattern recognition to map objects into a domain in which they can be compared. Usually, this domain is a vector space. It might also be a graph or a symbolic sequence or any other modality that allows the computation of distances between the represented objects. The quality of a…

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Choosing or learning a representation?

The field of pattern recognition studies automatic tools for the integration of existing knowledge and given observations to enriched knowledge applicable to future observations. In particular general techniques that are useful for a set of applications are of interest. In order to relate objects, they have to be considered in a common representation. Should this…

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A crisis in the theory of pattern recognition

The Russian scientist A. Lerner published in 1972 a paper under the title: “A crisis in the theory of Pattern Recognition”. This is definitely a title that attracts the attention of researchers interested in the history of the field. What was it to have appeared as the crisis? The answer is surprising, in short it…

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