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achievements of computer technologies. What is more, such systems do not fit the
theoretical frameworks of today's information collection and searching systems, so
when undertaking the development and practical implementation of Cognitive In-
formation Systems, the first task is to find, develop and research new theoretical
formalisms adequate for the jobs given to these systems. They will use the theo-
retical basis and conceptual formalisms developed for cognitive science by physi-
ology, psychology and philosophy (see Fig. 1), but they have to adjusted to the
new situation, namely the intentional initiation of cognitive processes in techno-
logical systems. Informatics has already attempted to create formalisms for sim-
pler information systems on this basis [2, 5]. In addition, elements of a cognitive
approach are increasingly frequently cropping up in the structure of new-
generation pattern classification systems [3, 6], although the adequate terminology
is not always used. On the other hand, some researchers believe that the cognitive
domain can be conquered by IT systems just as the researchers of simple percep-
tion and classification mechanisms have managed to transplant selected biological
observations into the technological domain, namely into artificial neural networks
[4]. However, the authors have major doubts whether this route will be productive
and efficient, as there is a huge difference in scale between neurobiological proc-
esses which are mapped by neural networks and mental processes which should be
deployed in cognitive information systems or cognitive pattern recognition ap-
proaches. The reason is that whereas neural networks are based on the action of
neurons numbering from several to several thousand (at the most), mental proc-
esses involve hundreds of millions of neurons in the brain, which is a significant
hindrance in any attempt to imitate them with computers. This is why it seems
appropriate and right to try to base the design of future Cognitive Information Sys-
tems on attempts at the behavioural modelling of psychological phenomena and
not on the structural imitation of neurophysiological processes.
The general foundations for the design of such systems have been the subject of
earlier publications [6, 7, 8]. However, it must be said that the methodology of de-
signing universal systems of cognitive interpretation has yet to be developed fully.
This applies in particular to systems oriented towards the cognitive analysis of
multimedia information. Overcoming the barrier between the form of multimedia
information (e.g. the shape of objects in the picture or the tones of sounds) and the
sense implicitly contained in this information requires more research initially ori-
ented towards detailed goals. Possibly, after some time, it will be possible to ag-
gregate the experience gained while executing these individual, detailed jobs into
a comprehensive, consistent methodology. However, for the time being, we have
to satisfy ourselves with achieving individual goals one after another. These goals
are mainly about moving away from the analysis of data describing single objects
to a more general and semantically deepened analysis of data presenting or de-
scribing various components of images or different images from the same video
sequence. Some good examples of such visual data analysis will be presented in
following chapters.
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