Classification of Real Estate Images using Bottleneck Features

Abstract

Image processing enhanced by deep learning is now being actively applied to real-world issues. The real estate industry, which owns lots of property information, also expects to develop new services using deep learning. In this paper, we present the classification methods for property images using bottleneck features generated by convolution networks (CNN), and experimentally show that we can achieve 88% accuracy in Top-1.