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About Deep Layer Aggregation
1. Deep Layer Aggregation (DLA) introduces two new network architectures, iterative deep aggregation (IDA) and hierarchical deep aggregation (HDA), to better fuse information across layers for visual recognition tasks. 2. IDA refines resolution and aggregates scale in a stage-by-stage manner by following the base network hierarchy. HDA assembles its own hierarchical structure of tree-connected skip connections to merge representations from different levels. 3. Experiments show that DLA improves performance over baseline ResNet, ResNeXt and DenseNet architectures on tasks like image classification, segmentation and detection, using fewer parameters and memory.
Detailed Information
| Author: | ['trí nguyễn'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 10 |
| Language: | English |
| Format: | |
| Price: | FREE |
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