Deep Learning Platforms in Food Recognition

Image content prediction with novel deep learning approaches is a hot research topic for many scientific disciplines. Image-based food types recognition and their ingredients is a particularly challenging task, since food dishes are typically deformable objects, usually including complex semantics, which makes the task of defining their structure very difficult. In this paper we introduce a novel web-based system that exploits commercial deep learning based platforms to predict image content for food recognition. In addition to that, the system combines the individual predictions of the platforms to produce more accurate results. Also, we provide a short assessment of the chosen platforms to determine the most efficient one, in the domain of food recognition. The paper is concluded by highlighting the key features of platforms and the advantages of the new presented system.