Name
Abstract | ||
|---|---|---|
Bringing machines up to human-level visual processing capabilities is an attractive research topic for decades. Deep neural networks (DNNs), inspired by the hierarchical structure of the human primary visual cortex at a macroscopic level, have achieved state-of-the-art performance in many applications. However, their practical applications remain limited due to the requisition of massive computing... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/IJCNN52387.2021.9534061 | 2021 International Joint Conference on Neural Networks (IJCNN) |
Keywords | DocType | ISSN |
Deep learning,Visualization,Biological system modeling,Microscopy,Neurons,Information processing,Visual systems | Conference | 2161-4393 |
ISBN | Citations | PageRank |
978-1-6654-3900-8 | 0 | 0.34 |
References | Authors | |
10 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuchen Wang | 1 | 1 | 2.39 |
| Xiaobin Wang | 2 | 0 | 0.34 |
| Hong Qu | 3 | 238 | 29.27 |
| Ya Zhang | 4 | 1340 | 91.72 |
| Yi Chen | 5 | 8 | 3.14 |
| xiaoling luo | 6 | 8 | 2.49 |