pandemonium architecture

The best known feature detection model is called the pandemonium architecture.

Pandemonium architecture was one of the first computational models in pattern recognition.

In principle, a pandemonium architecture can recognize any pattern.

Some researchers have also pointed out that the evidence supporting the pandemonium architecture has been very narrow in its methodology.

The basic idea of the pandemonium architecture is that a pattern is first perceived in its parts before the "whole".

Not surprisingly, the results often favored a hierarchal feature building model like the pandemonium architecture.

The pandemonium architecture was originally developed by Oliver Selfridge in the late 1950s.

Although not perfect, the pandemonium architecture influenced the development of modern connectionist, artificial intelligence, and word recognition models.

Generally, the results from these experiments matched the error predictions from the pandemonium architecture.

Based on the original pandemonium architecture, John Jackson has extended the theory to explain phenomena beyond perception.

The Hebbian model resembles feature-oriented theories like the pandemonium architecture in many aspects.

Additionally, some researchers have pointed out that feature accumulation theories like the pandemonium architecture have the processing stages of pattern recognition almost backwards.

The pandemonium architecture has been applied to solve several real-world problems, such as translating hand-sent Morse codes and identifying hand-printed letters.

Pandemonium architecture arose in response to the inability of template matching theories to offer a biologically plausible explanation of the image constancy phenomena.

A major criticism of the pandemonium architecture is that it adopts a completely bottom-up processing: recognition is entirely driven by the physical characteristics of the targeted stimulus.

This granted pandemonium architectures tremendous power because it is capable of recognizing a stimulus despite its changes in size, style and other transformations; without the presumption of an unlimited pattern memory.

However, it is rather difficult to judge the validity of this criticism because the pandemonium architecture does not specify how and what features are extracted from incoming sensory information, it simply outlines the possible stages of pattern recognition.

The critical difference between the two is that the image is directly compared against an internal representation in the template matching theories, whereas with the pandemonium architecture, the image is first diffused and processed at the featural level.

Although the pandemonium architecture arose as a response to address a major criticism of the template matching theories, the two are actually rather similar in some sense: there is a process where a specific set of features for items is matched against some sort of mental representation.

Although the pandemonium architecture is built on the fact that it can account for the image constancy phenomena, some researchers have argued otherwise; and pointed out that the pandemonium architecture might share the same flaws from the template matching models.