Mediterranean Food Image Recognition Using Deep Convolutional Networks

We present a new dataset of food images that can be used to evaluate food recognition systems and dietary assessment systems. The Mediterranean Greek food MedGRFood dataset consists of food images from the Mediterranean cuisine, and mainly from the Greek cuisine. The dataset contains 42,880 food images belonging to 132 food classes which have been collected from the web. Based on the EfficientNet family of convolutional neural networks, specifically the EfficientNetB2, we propose a new deep learning schema that achieves 83.4% top-1 accuracy and 97.8% top-5 accuracy in the MedGRFood dataset for food recognition. This schema includes the use of the fine tuning, transfer learning and data augmentation technique.