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Developing an education web site that can support students, researchers and staff in the area of Pattern Recognition has been one of the main activities during my tenure as chair of the Education Committee. Of course, advances in pattern recognition and its subfields means that developing the site will be a never-ending process. However, we believe that the current site is now well developed enough for general use.


What resources does the IAPR Education web site have?


The most important resources are for students, researchers and educators. These include lists with URLs to:

 Tutorials and surveys

 Explanatory texts

 Online demos


 Book lists

 Free code

 Course notes

 Lecture slides

 Course reading lists


 A list of course web pages at many universities


There are many areas for extension in the web pages, but they already link to more than 3000 resources. These resources are subdivided into five areas. Of course, the boundaries are never distinct, and we undoubtedly will also provoke a few dissenting opinions; however, we have tried to address the main work done by the IAPR community, as clustered into 3 core technology areas and 2 broad families of application areas:


1. Symbolic Pattern Recognition

2. Statistical Pattern Recognition

3. Machine Learning

4. 1D Signal Analysis

5. Computer vision/Image Processing/Machine Vision


What future developments do we expect?


We hope that in the next Education Committee cycle, two additional developments can take place. The first is to smooth the look and feel of the site, which has somewhat different styles in places because of the many contributors. The second development is one of substance: we would like to develop several example curricula for courses of different lengths, in the core technologies and for the application areas. Finally, the existing resources will be extended and refreshed (a never-ending process, no doubt).




Initial website development was by Christos Papadopoulos and Apostolos Antonacopoulos.

Content entry was Edinburgh University PhD students Kisuh Ahn, Edwin Bonilla, Lei Chen, Tim Hospedales, Gail Sinclair, and Narayanan Unny E, supervised by Bob Fisher.

Content advice supplied by by the 2006-8 Education Committee: Bruce Maxwell, Sudeep Sarkar, Xiaoyi Jiang, Laurent Heutte and Sergios Theodoridis.

Funding was provided by the EC funded euCognition network, the British Machine Vision Association and the UK's Engineering and Physical Sciences Research Council EPSRC.


by Bob Fisher (UK)

University of Edinburgh

Introducing the web site of the
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