Pattern recognition between science and engineering: A red herring?☆
Section snippets
Motivations
What is the nature of pattern recognition research? Is it an engineering enterprise or a scientific one? These and similar questions have been asked repeatedly during the (short) history of our field, and the community appears to be split into two parties.
On the one hand, we find those who adhere to a purely engineering perspective, with its emphasis on real-world problems and applications. This view, which is often implied by many a scholar and is revealed by the very structure of the most
Science and engineering: a tale of two myths
In the history of thought we find several misconceptions about science and engineering, two of which can be seen as enduring myths that accompanied the development of scientific and engineering activities for centuries. One views science as a well-demarcated endeavor totally committed to the discovery of (eternal) “truths,” while the other regards engineering simply as a practical activity which is never concerned with knowledge-for-knowledge’s sake [82]. In the past these ideas, which are
Pattern recognition: from science to technology and back
If we were to look for a contemporary research field that best exemplifies the interplay between science and technology, artificial intelligence would naturally suggest itself. But more than in other subfields of artificial intelligence, it is probably in pattern recognition and related areas (machine learning, computer vision, etc.) that one finds the most vivid manifestation of such an intimate relationship.
Perhaps the best example in this regard comes from the (troubled) history of neural
Discussion
What are the implications of these observations? Granted that the demarcation between science and technology appears to be more blurred and problematic than we use to think, what are we to make of this? The debates over the disciplinary status of a field of study are often regarded by practitioners as abstract discussions with little or no practical value. On the contrary, if taken seriously, we believe that the above considerations can offer researchers a fresh perspective that might lead the
Conclusions
With this paper we wanted to reopen a classic debate about the nature of pattern recognition research. Over the past few decades, in fact, two opposite tendencies have emerged: one which considers our field to be a purely engineering or technological discipline, the other which, on the contrary, sees ours as a scientific enterprise. These positions seem irreconcilable, for the simple reason that the two camps are traditionally felt to have different goals, one aiming at “use,” the other aiming
Acknowledgments
We would like to thank Gori and Roli for many stimulating discussions on the notion of progress and performance evaluation in computer vision and pattern recognition, and the anonymous reviewers for their constructive comments.
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This paper has been recommended for acceptance by Gabriella Sanniti di Baja.