Research Article
Application of Recurrent Neural Network Algorithm in Intelligent Detection of Clinical Ultrasound Images of Human Lungs
| ConvNet configuration |
| A | A-LRN | B | C | D | E | 11 weight layers | 11 weight layers | 13 weight layers | 16 weight layers | 16 weight layers | 19 weight layers |
| Input (224 × 224 RGB image) | conv3-64 | conv3-64 | conv3-64 | conv3-64 | conv3-64 | conv3-64 | LRN | conv3-64 | conv3-64 | conv3-64 | conv3-64 |
| Maxpool | conv3-128 | conv3-128 | conv3-128 | conv3-128 | conv3-128 | conv3-128 | | conv3-128 | conv3-128 | conv3-128 | conv3-128 |
| Maxpool | conv3-256 | conv3-256 | conv3-256 | conv3-256 | conv3-256 | conv3-256 | conv3-256 | conv3-256 | conv3-256 | conv3-256 | conv3-256 | conv3-256 | | | | conv1-256 | conv3-256 | conv3-256 | | | | | | conv3-256 |
| Maxpool | conv3-512 | conv3-512 | conv3-512 | conv3-512 | conv3-512 | conv3-512 | conv3-512 | conv3-512 | conv3-512 | conv3-512 | conv3-512 | conv3-512 | | | | conv1-512 | conv3-512 | conv3-512 | | | | | | conv3-512 |
| Maxpool | conv3-512 | conv3-512 | conv3-512 | conv3-512 | conv3-512 | conv3-512 | conv3-512 | conv3-512 | conv3-512 | conv3-512 | conv3-512 | conv3-512 | | | | conv1-512 | conv3-512 | conv3-512 | | | | | | conv3-512 |
| Maxpool |
| FC-4096 | FC-4096 | FC-1000 | Soft-max |
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