Deep Learning for Vision Systems by Mohamed Elgendy

Author:Mohamed Elgendy [Elgendy, Mohamed]
Language: eng
Format: epub, pdf
Publisher: Manning Publications Co.
Published: 0101-01-01T00:00:00+00:00

5.6.3 ResNet implementation in Keras

You’ve learned a lot about residual blocks so far. Let’s add these blocks on top of each other to build the full ResNet architecture. Here, we will implement ResNet50: a version of the ResNet architecture that contains 50 weight layers (hence the name). You can use the same approach to develop ResNet with 18, 34, 101, and 152 layers by following the architecture in figure 5.24 from the original paper.

Figure 5.24 Architecture of several ResNet variations from the original paper

We know from the previous section that each residual module contains 3 × 3 convolutional layers, and we now can compute the total number of weight layers inside the ResNet50 network as follows:

Stage 1: 7 × 7 convolutional layer

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.