Applications of RAM based networks

For any approach to be worth while studying, demonstrable proof of its utility on practical problems is essential. This section contains a number of practical studies. All the applications are found in image processing, the traditional area for the successful use of RAM based methods (as in its original use). The main reason for this is that the methods scale well to the large input data sizes needed for image analysis problems. The final paper examines the implementation of ADAM, a RAM based network for image analysis, on a parallel system of transputers.

The first paper by O'Keefe and Austin shows there use in finding features in fax images. A problem that makes use of the potentially fast processing and noise tolerant properties as it is applied to faxes that are sent via typical fax machines. In addition it illustrates how RAM based methods compare with traditional object recognition methods.

Texture recognition is examined by Hepplewhite and Stonham, how introduce a novel pre-processing method and compare a number of existing N tuple pre-processing methods for this task.

RAM based networks are particularly suitable for small mobile robots as shown by Bishop, Keating and Mitchell, who demonstrate that a compound, insect like, eye can be created and used to control a simple robot.

Feature analysis is a vital part of machine vision explored by Clarkson and Ding. They show how a pRAM based network can be used to find features in a fingerprint recognition system. In addition, they show how noise injection can be used to improve performance of the method.

The use of colour in the detection of danger labels is investigated by Linneberg, Andersen, Jorgensen and Chistensen where the power of the N tuple method to solve real problems is demonstrated.

The problems involved in exploring complex images using saccadic image scanning methods is explored by Ntourntoufis and Stonham. They extend the MAGNUS network presented in section one to dealing with multiple objects in a 'Kitchen World' scene. Illustrating that iconic internal representations used in MAGNUS can be used to control image understanding systems.

Finally, hand written text is examined in the chapter by De Carvalho and Bisset, where the SOFT and GSN RAM based methods are combined in a modular approach to a difficult classification problem.