The self-organizing desk is a system that enhances a physical desk-top with electronic information. It can remember, organize, update, and manipulate the information contained in the documents on a desk. The system consists of a simple robot eye that can survey the desk, a module for smart extraction of information from the images taken by the robot, a module for representing this information i...

It has been proved that in one-dimensional cases, the weights of Kohonen’s self-organizing maps (SOM) will become ordered with probability 1; once the weights are ordered, they cannot become disordered in future training. It is difŽcult to analyze Kohonen’s SOMs in multidimensional cases; however, it has been conjectured that similar results seem to be obtainable in multidimensional cases. In t...

Image compression helps in storing the transmitted data in proficient way by decreasing its redundancy. This technique helps in transferring more digital or multimedia data over internet as it increases the storage space. It is important to maintain the image quality even if it is compressed to certain extent. Depends upon this the image compression is classified into two categories: lossy and ...

The basic SOM is indi erent to the ordering of the input patterns. Real data, however, is often sequential in nature thus context of a pattern may signi cantly in uence its correct interpretation. One simple SOM model that takes the context of a pattern into account is the Temporal K ohonen Map (TKM),which was modi ed into the Recurrent Self Organizing Map (RSOM). We sho w analytically and with...

A technique for segmentation of images of baked good is presented. The technique employs a Self-Organising Map to identify the characteristic colour development curve (bake curve) for each product. Segmentation is based upon the colour information contained in the bake curve. The technique is trained with only positive exemplars of the product.