Deep Learning for Classifying Food Dishes.
This was done as part of Stanford University's Spring 2017 course CS231N : Convolutional Neural Networks for Visual Recognition
We consider the problem of classifying food dishes. Food items have unique characteristics - they come in different colors and shapes, can be clustered into groups (e.g. fruits, vegetables), and can be combined in several ways to prepare a meal etc. This makes images of food dishes particularly interesting to classify. We show that convolutional neural networks are quite suitable for this task, and outperform traditional machine learning approaches in classifying food dishes.
The full paper is here