The goal of this work is to classify histopathology images into benign and malignant.  They use the BreaKHis and IICBU 2008 lymphoma datasets.

They use a VGG network for feature extraction from each image. Then on these VGG feature vectors they learn [Fisher Vectors ](https://prateekvjoshi.com/2014/08/23/image-classification-using-fisher-vectors/) which they use to make a prediction.

It is unclear why Fisher Vectors are more useful than the fully connected layers of the VGG net that they replace. It is not clear how much analysis was performed for the VGG baseline. Also, as a baseline a VGG network should have been trained from scratch to extract domain specific features. 

Poster:
https://i.imgur.com/fgzmeYv.png