ENet Dilated Bottleneck
Introduced by Paszke et al. in ENet: A Deep Neural Network Architecture for Real-Time Semantic SegmentationENet Dilated Bottleneck is an image model block used in the ENet semantic segmentation architecture. It is the same as a regular ENet Bottleneck but employs dilated convolutions instead.
Source: ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
Latest Papers
Tasks
| TASK | PAPERS | SHARE |
|---|---|---|
| Semantic Segmentation | 10 | 31.25% |
| Autonomous Driving | 4 | 12.50% |
| Instance Segmentation | 2 | 6.25% |
| Scene Understanding | 2 | 6.25% |
| Food Recognition | 1 | 3.13% |
| Image Classification | 1 | 3.13% |
| Self-Driving Cars | 1 | 3.13% |
| Autonomous Vehicles | 1 | 3.13% |
| Knowledge Distillation | 1 | 3.13% |
Usage Over Time
Components
| COMPONENT | TYPE |
|
|---|---|---|
1x1 Convolution
|
Convolutions | |
Batch Normalization
|
Normalization | |
Dilated Convolution
|
Convolutions | |
Max Pooling
|
Pooling Operations | |
PReLU
|
Activation Functions | |
SpatialDropout
|
Regularization |