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About Deep ResNet
This document proposes a new deep neural network architecture called Pyramidal Residual Networks (PyramidNets). PyramidNets gradually increase the feature map dimension at all units, rather than sharply increasing it only at downsampling units like conventional networks. This distributes the feature extraction burden across all units instead of concentrating it at downsampling units. The paper finds that deleting units with downsampling does not significantly degrade PyramidNets' performance, unlike other networks. It also introduces a novel pyramidal residual unit that further improves classification accuracy over standard residual networks. Experiments show PyramidNets achieve superior generalization compared to original residual networks.
Detailed Information
| Author: | ['Avanish Singh'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 9 |
| Language: | English |
| Format: | |
| Price: | FREE |
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