… a machine learning system for food category recognition, … In general, at present, we can
divide the existing datasets … This part of the data is called the Food201-segmented dataset. …

… strong capabilities to process image segmentation tasks. Fully … , and different training datasets
on food classification accuracy. It … on food with deep learning methods, to present precise …

… were presented: Food-101 and a database of Indian foods, … out in two public datasets:
Food-101 as a dataset for a large … , image segmentation, extraction of features, image …

… as meal assistance robot arm, we generate synthetic data using the … To address the presented
difficulties, we employed two … a deep neural network and constructed a synthetic dataset …

… common deep learning methods used for food classification, … for food classification, introducing
the main databases of food … used for image classification [5], [19], image segmentation [20]…

… deep learning architecture for food image recognition. Next, we present our ZRUN RQ
IDNH-food … problem, we manually segmented each image in the recognition dataset into different …

… Dataset is a key step in developing deep learning based methods. We hope our dataset can
inspire more efforts for the task of food image … In Table 2, we present the statistic numbers. …

… taking a picture of a meal for food recognition and logging. … multi-task learning, are presented
with new empirical insights. … segmentation on the Food-101 dataset. Similar to [24], image …

… dataset and provide relevant baselines with deep learning … ] require users to enter their meal
information manually. A study … research in food classification by introducing a new dataset of …

… introduce a new dataset containing 20 different food categories … food-related tasks such as
food localization, segmentation, … We evaluated several hand-crafted and deep learning based …