| id |
b83a |
| authors |
Benoudjit A, Derix C and Coates P |
| year |
2004 |
| title |
Human perception and space classification: The Perceptive Network |
| source |
Proceedings of the Generative Arts conference, Milan, 2004 |
| summary |
This paper presents a computer model for space perception, and space classification that is built around two artificial neural networks (ANN). This model is the first known application in architecture, where a self-organized map (SOM) is used to create a space classification map on the base of human perception criteria. This model is built with the aim to help both the space designers (architects, interior designer and urban designers), and the space users to gain a better understanding of the space in particular, and the environment where they evolve in general. This work is the continuity of an outgoing work started in the CECA by C. Derix around Kohonen network. |
| keywords |
neural network, self-organised feature map, perception, spatial configuration |
| series |
other |
| type |
normal paper |
| email |
|
| more |
http://www.generativeart.com/ |
| full text |
 file.pdf (916,489 bytes) |
| references |
Content-type: text/plain
|
| last changed |
2012/09/20 21:28 |
|
