Name
Title | ||
|---|---|---|
Parasitic Network: Learning-Based Network Downsizing of Very Deep Neural Networks for Computer Vision |
Abstract | ||
|---|---|---|
In recent research on deep neural network (DNN), network downsizing is one of practical issues for computational and memory efficiency. Specifically, downsizing or compression of networks minimizing the performance degradation becomes a critical problem for deployment of DNNs on resource-limited environments such mobile or embedded platforms. In this paper, we propose a compressed network called the parasitic network (PN) inspired by the relationship between a parasite and host in nature. The concept of the parasitic network is straightforward. The host network provides their mapping results in each layer to the PN as a feed. The PN that much shallower than the host network is trained based on given information from the host network. We demonstrate efficiency of our approach to the network downsizing in image classification and object detection problems which have conquered by the deeper and bigger networks. The experimental results show that PN can provide sample performance to their host network even though their architectural scale is much smaller. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ICCAIS.2018.8570503 | 2018 International Conference on Control, Automation and Information Sciences (ICCAIS) |
Keywords | Field | DocType |
Network downsizing,network compression,parasetic network | Object detection,Architect's scale,Software deployment,Control engineering,Host (network),Engineering,Artificial neural network,Contextual image classification,Deep neural networks,Distributed computing | Conference |
ISSN | ISBN | Citations |
2475-790X | 978-1-5386-6021-8 | 0 |
PageRank | References | Authors |
0.34 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jongmin Yu | 1 | 9 | 4.54 |
| Duyoung Kim | 2 | 0 | 0.34 |
| Moongu Jeon | 3 | 456 | 72.81 |