In this section, we will show you how to take advantage of many pre-trained models from Caffe Model Zoo (https://github.com/BVLC/caffe/wiki/Model-Zoo). There are lots of Caffe models for different tasks with all kinds of architectures. After converting these models to TensorFlow, you can use it as a part of your architectures or you can fine-tune our model for different tasks. Using these pre-trained models as initial weights is an effective approach for training instead of training from scratch. We will show you how to use a caffe-to-tensorflow approach from Saumitro Dasgupta at https://github.com/ethereon/caffe-tensorflow.
However, there are lots of differences between Caffe and TensorFlow. This technique only supports a subset of layer types from Caffe. Even though there are some Caffe architectures that are verified by the author of this project such as...
