Name
Abstract | ||
|---|---|---|
The aim of the research introduced in this paper is the development of a hybrid vision system architecture based on a unified neural network platform and a query-based database that shares their noise-tolerant, learning and interactive properties. The function of the system is to model and interpret the behaviour of a class of cancerous cells by (a) extracting cell features from the images, (b) classifying the temporal and social behaviour of the cells, and (c) driving the interpretation search according to the needs of the user. This paper gives a description of the application and the proposed system and presents the results drawn from two neural network architectures used for the extraction of cell centroid areas from images. Both networks are implemented on a Distributed Array of Processors (DAP) and trained using the backpropagation learning algorithm. |
Year | DOI | Venue |
|---|---|---|
1993 | 10.1016/0925-2312(93)90009-R | Neurocomputing |
Keywords | Field | DocType |
Hybrid architecture,neural networks,backpropagation,image interpretation system,motion understanding | Architecture,Social behaviour,Pattern recognition,Machine vision,Computer science,Artificial intelligence,Backpropagation,Artificial neural network,Machine learning,Centroid | Journal |
Volume | Issue | ISSN |
5 | 4-5 | 0925-2312 |
Citations | PageRank | References |
2 | 0.43 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexandra Psarrou | 1 | 199 | 27.14 |
| Hilary Buxton | 2 | 491 | 135.93 |