Name
Abstract | ||
|---|---|---|
Visual context plays a significant role in humans' gaze movement for target searching. How to transform the visual context into the internal representation of a brain-like neural network is an interesting issue. Population cell coding is a neural representation mechanism which was widely discovered in primates' visual neural system. This paper presents a biologically inspired neural network model which uses a population cell coding mechanism for visual context representation and target searching. Experimental results show that the population-cell-coding generally performs better than the single-cell-coding system. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-15819-3_22 | ICANN (1) |
Keywords | Field | DocType |
internal representation,single-cell-coding system,visual context,brain-like neural network,population cell coding,population cell,visual neural system,visual context representation,neural network model,neural representation mechanism,neural coding network,neural network,neural code,neural coding,code generation | Population,Nervous system network models,Computer science,Neural coding,Recurrent neural network,Time delay neural network,Artificial intelligence,Neural decoding,Deep learning,Artificial neural network,Machine learning | Conference |
Volume | ISSN | ISBN |
6352 | 0302-9743 | 3-642-15818-8 |
Citations | PageRank | References |
2 | 0.41 | 5 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jun Miao | 1 | 220 | 22.17 |
| Baixian Zou | 2 | 6 | 1.88 |
| Laiyun Qing | 3 | 337 | 24.66 |
| Lijuan Duan | 4 | 215 | 26.13 |
| Yu Fu | 5 | 110 | 3.38 |