In this directory, we aim to implement the VGG family of convolutional neural network (CNN) models for image classification, including the well-known VGG-16 and VGG-19 models, to be tested with the ImageNet dataset.
Available implementations:
| Description | Library | Notebook | |
|---|---|---|---|
| v1 | Basic impl | Keras |    |
Implementation notes for v1:
- We haven't yet trained or tested this network (work in progress).
Our implementation is based on the following paper:
- Karen Simonyan and Andrew Zisserman. "Very deep convolutional networks for large-scale image recognition." arXiv preprint arXiv:1409.1556 (2014).
Note: this paper was also published in ICLR 2015.
This paper is available via:
See also:
- VGG report from the authors - links to download models
- Papers with Code