Skip to content

Visualizing layer output of AlexNet model trained on cifar-10 dataset

Notifications You must be signed in to change notification settings

ishanExtreme/AlexNet-Visualization

Repository files navigation

AlexNet-Visualization

Visualizing layer output of AlexNet model trained on cifar-10 dataset

Architecture

Official Paper

Model Summary

Trained on cifar-10 dataset

Performance

loss: 0.5992 - accuracy: 0.8075 - val_loss: 1.3247 - val_accuracy: 0.7012(Trained for 18 epochs)

Summary

Visualization

Original Image

Layer-1(conv2D)

Below are first five filters of Layer-1 resized to (224,224) pixels

Layer-4(conv2D)

Below are first five filters of Layer-4 resized to (224,224) pixels

Layer-7(conv2D)

Below are random five filters of Layer-7 resized to (224,224) pixels

Layer-11(conv2D)

Below are first five filters of Layer-11 resized to (224,224) pixels

Try it yourself on different images on google colab or on local system by using checkpoint and AlexNet.ipynb in the repository

About

Visualizing layer output of AlexNet model trained on cifar-10 dataset

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published