Image Model Blocks
Inception-ResNet-v2-B
Introduced by Szegedy et al. in Inception-v4, Inception-ResNet and the Impact of Residual Connections on LearningInception-ResNet-v2-B is an image model block for a 17 x 17 grid used in the Inception-ResNet-v2 architecture. It largely follows the idea of Inception modules - and grouped convolutions - but also includes residual connections.
Source: Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| General Classification | 3 | 10.34% |
| Image Classification | 3 | 10.34% |
| Classification | 2 | 6.90% |
| Machine Translation | 2 | 6.90% |
| Breast Cancer Detection | 1 | 3.45% |
| Classifier calibration | 1 | 3.45% |
| Fine-Grained Image Classification | 1 | 3.45% |
| Fine-Grained Image Recognition | 1 | 3.45% |
| Activity Recognition | 1 | 3.45% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
1x1 Convolution
|
Convolutions | |
Convolution
|
Convolutions | |
ReLU
|
Activation Functions | |
Residual Connection
|
Skip Connections |
